Program Report for 2000

Contents

ABOUT THIS REPORT v TRUSTEES vii PERSONNEL ix ABBREVIATIONS AND ACRONYMS xxiii RESEARCH PROGRAMS 1 Irrigated rice ecosystem 3 Rainfed lowland rice ecosystem 25 Upland rice ecosystem 49 Cross-ecosystems research 65 RICE GENETIC RESOURCES: CONSERVATION, SAFE DELIVERY, AND USE 101 ACCELERATING THE IMPACT OF RICE RESEARCH 111 AFFILIATIONS OF COLLABORATING RESEARCHERS 130 RESEARCH SUPPORT SERVICES 131 PUBLICATIONS AND SEMINARS 139 STAFF CHANGES 157 FINANCES 163 WEATHER SUMMARY 165

About this report

A long tradition of technical reporting on rice research at IRRI comes to an end with this 2000 Program Report. After 38 annual issues—either as the Annual Report (1962-88) or the Program Report (1989-2000)—this series will cease publication with this installment. By maintaining and improving various other IRRI publication series (Discussion Paper, Technical Bulletin, and Limited Proceedings), in addition to the availability of refereed journal articles (e.g., approximately 150 listed for 2000 in this Program Report), the possible compilation of certain sets of journal articles by IRRI, articles in formal IRRI workshop and symposium proceedings (five or six annually), and dozens of proceedings from other institutions, IRRI management feels that technical research reporting to other rice scientists will be adequately covered in the future. Beginning in 2002 (i.e., reporting for 2001), a revamped Report of the Director General will include the detailed staff list, publications and seminars, and donor contribution details that have, up to now, always appeared in this Program Report. This year's report brings closure to the Mediumterm Plan for 1998-2000 and—as in recent years— some programs present a selective, rather than allencompassing report of projects in the research and international programs. For these, capsule summaries are provided. An added note: IRRI is currently digitizing its historic set of scientific publications that cover a period of 41 years. Included in this collection, which will eventually be available online in portable document format (pdf), is this unique set of research reports that provides an unbroken string of scientific investigations in rice over the last four decades.

Projects not reported on in detail are listed at the end of each program section. The 2000 listings include point summaries of accomplishments that were gleaned from the April 2001 Report of the Director General. All research activities are reported under one of the following: Irrigated Rice Ecosystem; Rainfed Lowland Rice Ecosystem; Upland Rice Ecosystem; Cross-ecosystems Research; and Rice Genetic Resources: Conservation, Safe Delivery, and Use. Other activities are reported under Accelerating the Impact of Rice Research (Strengthening partnership with NARES; Delivery of knowledge-intensive technologies: Crop and Resource Management Network; Collecting, exchanging, and distributing knowledge and information about rice; and Human capital development of NARES rice professionals). The report is limited to activities that have reached a reportable stage involving analysis, interpretation, and conclusions. A few significant interim results are reported because they may be useful to other rice workers. Information on the research programs can be obtained from the program leaders or the research organizational units noted in the table of contents for each program, represented by these abbreviations: AE = Agricultural Engineering CSWS = Crop, Soil, and Water Sciences EPP = Entomology and Plant Pathology GRC = Genetic Resources Center PBGB = Plant Breeding, Genetics, and Biochemistry SS = Social Sciences Programs for accelerating the impact of rice research are administered through these entities, which can be contacted for further information:

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Communication and Publications Services, Visitors and Information Services, and Library and Documentation Services (Collecting, exchanging, and distributing knowledge and information about rice) Training Center (Human capital development of NARES rice professionals) International Programs Management Office (Strengthening partnership with NARES) Crop and Resource Management Network (Delivery of knowledge-intensive technologies) Names of IRRI research staff and collaborators are given for most projects or activities. The affiliations of collaborating researchers are listed on page 130. Names without a footnote are those of IRRI staff. Abbreviations and acronyms used in this report are listed on pages xxiii-xxiv. In addition, all names and terms are spelled out on first use in each program and abbreviations are used thereafter. The report uses the International System of Units (SI). Monetary units are usually in U.S. dollars ($); if not, exchange rates are provided. Control or check normally means an untreated control and all results reported are based on scientifically accepted experimental design. Grain yield is calculated as rough rice, and protein content as a percentage of brown rice, at 14% moisture content. Yield refers to grain yield unless otherwise noted. Fertilizer amounts are given in terms of the elements (N,P, K, Zn, etc.), not in oxide formulation (P2O5, K2O, etc.). Pedigrees

are indicated by a slant bar (/) rather than by a multiplication sign (×). For example, (PTB33 × IR30) × IR36 is written PTB 33/IR30/IR36. Fourth and further crosses are designated /4/, /5/, and so on. Backcrosses are designated by an asterisk (*) and a number that indicates the number of times the recurrent parent is crossed to the other parent. The asterisk and the number are placed adjacent to the crossing symbol that divides the current and donor parents. Unless otherwise noted, scoring of morphological characters and of damage attributed to rice pests and physiochemical stresses is based on scales in Standard evaluation system for rice (SES), 4th edition, 1996. Copies are available from the International Network for Genetic Evaluation of Rice, IRRI. In tables, a single asterisk (*) means a difference at the 5% level of significance, and a double asterisk (**) means a significant difference at the 1% level; ns means not significant. Unless otherwise stated, separation of means in table columns is by Duncan’s multiple range test at the 5% level. This report normally uses generic names of chemicals. Use of a commercial brand name does not constitute endorsement. A thumb index on the back cover provides access to each program. To use it, bend the book slightly and follow the margin index to the page with the back edge margin.

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Trustees

Board Chair DR. ROELOF RABBINGE Chairman and Professor Department of Theoretical Production Ecology Wageningen Agricultural University P.O. Box 430, 6700 AK Wageningen The Netherlands E-mail: [email protected] Members DR. SHIGEMI AKITA Professor The University of Shiga Prefecture 2500 Hassaka-cho, Hikone Shiga 522-8533, Japan Tel: (81-749) 28-8200 HON. EDGARDO J. ANGARA (EX OFFICIO) Secretary Department of Agriculture Elliptical Road, Diliman, Quezon City 3008 Philippines Fax: (63-2) 929-8183 or 928-5140 MS. MAKIKO ARIMA-SAKAI President Yokohama Women’s Association for Communication and Networking Forum Yokohama Branch Landmark Tower 13 F, 2-2-1-1 Minato Mirai, Nishi-ku, Yokohama 220-81, Japan E-mail: [email protected]. DR. SJARIFUDIN BAHARSJAH Independent Chair Food and Agriculture Organization of the United Nations Komplek Perumahan Pejabat Tinggi Jalan Duta Permai V/1, Pondok Indah, Jakarta, Indonesia E-mail: [email protected]

DR. RONALD P. CANTRELL (EX OFFICIO) Director General International Rice Research Institute DAPO Box 7777 Metro Manila, Philippines E-mail: [email protected] MRS. ANGELINE S. KAMBA 3 Hogsback Lane P.O. Box BW 699, Borrowdale Harare, Zimbabwe E-mail: [email protected] DR. LENE LANGE Director Molecular Biotechnology Novozymes A/S Krogshoejvej 36, bldg 1AMS.04 DK-2880 Bagsvaerd, Denmark E-mail:[email protected] DR. FRANCISCO NEMENZO (EX OFFICIO) President University of the Philippines System Diliman, Quezon City, Philippines E-mail: [email protected] DR. CALVIN O. QUALSET Director Genetic Resources Conservation Program Division of Agriculture and Natural Resources University of California One Shields Avenue Davis, California 95616-8602, United States E-mail: [email protected] DR. SIENE SAPHANGTHONG Minister Ministry of Agriculture and Forestry P.O. Box 811 Vientiane, Lao PDR Fax: (856-21) 412-344

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DR. EMANUEL ADILSON SOUZA SERRÃO Director General EMBRAPA Eastern Amazon CPATU/EMPBRAPA Caixa Postal 48 66.420 Belém, Pará, Brazil E-mail: [email protected] DR. E.A. SIDDIQ National Professor (ICAR) Directorate of Rice Research Rajendranagar Hyderabad 500030, Andhra Pradesh, India E-mail: [email protected] DR. JIAN SONG Vice Chairman Chinese People’s Political Consultative Conference, and President, Chinese Academy of Engineering Sciences 3 Fuxing Road, Beijing 100038, China Fax: (86-10) 6852-3054 E-mail: [email protected]. MR. MECHAI VIRAVAIDYA Chairman Population and Community Development Association 8 Sukhumvit 12, Bangkok 10110, Thailand Fax: (66-2)229-4632

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Personnel

Administrative staff
Ronald P. Cantrell, PhD, director general James T. McMahon, MS, assistant director general1 Kenneth S. Fischer, PhD, deputy director for research1; special adviser4 Mahabub Hossain, PhD, interim deputy director general for research6 William G. Padolina, PhD, deputy director general for partnertships (from director for external relations)4 Paulette Coburn, MS, director for administration and human resources1 Ian M. Wallace, MLS, interim director for administration and human resources Gordon B. MacNeil, MBA, director for finance Henrik Egelyng, PhD, institutional issues specialist4 Mercedita A. Sombilla, PhD, head, Liaison, Coordination, and Planning Duncan Macintosh, BS, head, Public Awareness4 Gelia T. Castillo, PhD, consultant Fernando A. Bernardo, PhD, consultant4 Orlando G. Santos, MPS, consultant Benito S. Vergara, PhD, consultant3

Imelda R. Barredo, BS, research technician III Eduardo L. Secretario, research technician III Benedicto S. Alborida, research technician II Policarpio S. Barbadillo, research technician II Edgardo T. Diaz, research technician II Luis L. Malabayabas, research technician II Vicente Q. Oruga, research technician II

Agronomy, Plant Physiology, and Agroecology
Osamu Ito, PhD, plant physiologist and head1 James E. Hill, PhD, agronomist and program leader, irrigated rice ecosystem, and head4 Andrew Martin Mortimer, PhD, weed ecologist and deputy head Colin M. Piggin, PhD, program leader, upland rice and rainfed lowland rice ecosystems1 Shaobing Peng, PhD, crop physiologist John E. Sheehy, PhD, systems modeler and crop ecologist Virendra Pal Singh, PhD, agronomist Leonard J. Wade, PhD, agronomist Renee Lafitte, PhD, plant physiologist Motohiko Kondo, MS, agronomist1 Keith S. Fahrney, PhD, upland agronomist1 Thomas George, PhD, IRS seconded from NifTAL Guy F. Trebuil, PhD, IRS seconded from CIRAD Pierre L. Siband, PhD, IRS seconded from CIRAD4 Jean Christophe Castella, PhD, IRS seconded from IRD Alan K. Watson, PhD, IRS seconded from McGill University Reimund P. Roetter, PhD, systems network coordinator Daniel C. Olk, PhD, affiliate scientist (Jan-Apr) and consultant (May-Dec) Maria Olofsdotter-Gunnarsen, PhD, affiliate scientist Akihiko Kamoshita, PhD, project scientist1 Satoshi Kubota, PhD, project scientist Lumin Liu, PhD, project scientist Chantal Loyce, PhD, project scientist4 Veeragathipillai Manoharan, PhD, project scientist Sanjay Singh, PhD, project scientist4 Pompe Sta. Cruz, PhD, project scientist
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Agricultural Engineering
Mark A. Bell, PhD, interim head Robert R. Bakker, PhD, affiliate scientist4 Mark Boru Douthwaite, MS, project scientist1 Dante B. de Padua, PhD, consultant Arnold R. Elepaño, PhD, consultant Christopher Meek, MBA, consultant4 Volker Hammen, visiting collaborator Romualdo C. Martinez, visiting collaborator Eugenio C. Castro, Jr., MS, assistant scientist II Paterno C. Borlagdan, MS, assistant scientist II Philip B. Cedillo, BS, assistant scientist I Reynaldo C. Billate, BS, researcher Edna B. Razote, BS, researcher Rodolfo A. Angco, CAD supervisor Elenita C. Suñaz, BS, administrative coordinator Ricardo M. Hernandez, BS, lead research technician

Jianchang Yang, PhD, project scientist1 Barney P. Caton, PhD, visiting scientist3 Theodore C. Foin, PhD, visiting scientist3 Motoyuki Hagiwara, PhD, visiting scientist4 Kuniyuki Saitoh, PhD, visiting scientist1 Vu Hai Nam, PhD, GIS specialist, consultant3 Christian Baron, PhD, consultant3 Michael Dingkuhn, PhD, consultant3 Nico de Ridder, MS, consultant3 Christoph Dreiser, PhD, consultant3 Donatus Jansen, PhD, consultant3 Peter L. Mitchell, PhD ,consultant3 M.V.R. Murty, PhD, consultant Martin van Ittersum, PhD, consultant3 Daniel van Kraalingen, MS, consultant3 Hendrika H. van Laar, PhD, consultant3 Benjamin K. Samson, Jr., PhD, consultant3 Romeo M. Visperas, MS, senior associate scientist Serafin T. Amarante, MS, assistant scientist II Helen Grace S. Centeno, MS, assistant scientist II Evangelina S. Ella, MS, assistant scientist II Joel D. Janiya, MS, assistant scientist II Maria Rebecca C. Laza, MS, assistant scientist II Rosario T. Lubigan, MS, assistant scientist II Rogelio D. Magbanua, MS, assistant scientist II Ofelia S. Namuco, MS, assistant scientist II Domingo C. Navarez, MS, assistant scientist II Rolando O. Torres, MS, assistant scientist II Gemma Mercedes O. Belarmino, BS, assistant scientist I Mary Jacqueline A. Dionora, MS, assistant scientist I Ana A. Eusebio, MS, assistant scientist I Alice G. Laborte, MS, assistant scientist I Eufrocino V. Laureles, MS, assistant scientist I Teodoro R. Migo, BS, assistant scientist I Paquito P. Pablico, MS, assistant scientist I Reynaldo C. Rodriguez, MS, assistant scientist I Marianne I. Samson, MS, assistant scientist I Joel D. Siopongco, BS, assistant scientist I Jonathan T. Quiton, MS, assistant scientist I Lolita L. Garcia, MS, program coordinator Ma. Angeles M. Quilloy, BS, program coordinator Ma. Theresa L. Tenorio, BS, administrative coordinator Leila H. Herbano, BS, administrative coordinator Ruth A. Agbisit, BS, researcher Abigail Elmido, BS, researcher4 Darryl V. Aragones, BS, researcher James A. Egdane, BS, researcher Jaime E. Faronilo, M Agr, researcher Julie Mae Criste Aimee D. Cabrera, BS, researcher Maridelle A. Dizon, BS, researcher Glenn D. Dimayuga, BS, researcher Anaida B. Ferrer, BS, researcher Carmelo O. Garcia, BS, researcher Donna F. Holt, BS, researcher Cecilia V. Lopez, AB, researcher Jaime L. Padilla, MS, researcher Zenaida P. Pascual, BS, researcher

Rico R. Pamplona, MS, researcher4 Arnel L. Sanico, BS, researcher Nemesio U. Trillana, MS, researcher Brenda S. Tubaña, BS, researcher Rachel V. Abrenilla, secretary II7 Carmelita R. Dilag, BS, secretary II Emma A. Fabian, AB, secretary II Lita L. Katimbang, secretary II Eva P. Reyes, AB, secretary II Susan M. Telosa, AB, secretary II1 Corazon E. Bambase, BS, secretary II Jovencita L. Biker, AB, secretary II Arlene D. de la Cruz, AB, secretary I Rosalie M. Laude, BS, secretary I Edna R. Reyes, secretary I Feliciano A. Cervantes, BS, lead research technician Pedro N. Gapas, BS, lead research technician Dominador P. Alejandro, research technician III Emiliano M. Barcial, research technician III Hilario H. de la Rosa, research technician III Teodoro M. Delgado, research technician III Donato V. Lanwang, research technician III Lamberto V. Licardo, research technician III Anicio P. Macahia, research technician III Victor R. Micosa, research technician III Gaudencio A. Sulit, research technician III Rodolfo M. de los Reyes, research technician III Artemio V. Madrid, Jr., research technician III Rogelio V. Reyes, research technician III Feliciano R. Fagela Jr., research technician III Edsel T. Moscoso, research technician III Jorge L. Alvarez, research technician III Leonardo R. Holongbayan, research technician III Onofre A. Mendoza, research technician III Rene M. Panopio, research technician III Maximo L. Pelagio, research technician III Deogracias, S. Llanto, data encoder Anthony T. Pulpulaan, data encoder1 Benjamin C. Nuñez, Jr., IT technician Nelson L. Abiog, research technician II Manolo S. Balanial, research technician II Siena B. Calibo, research technician II1 Ricardo S. Catangay, research technician II Melchor R. Comia, research technician II Arturo L. Crisostomo, research technician II Leodegario O. dela Rosa, research technician II Macario W. del Valle, research technician II Cesario B. de Mesa, Jr., research technician II Edwin P. Dizon, research technician II Roland N. Dizon, research technician II Rogelio T. Lapastora, Jr., research technician II Victor H. Lubigan, research technician II Ramon B. Masajo, research technician II Enrique F. Monserat, research technician II1 Guido M. Ramos, research technician II Fernando C. Salisi, research technician II Emeteria G. Sanchez, research technician II Lino B. Tatad, research technician II Nicanor L. Turingan, research technician II

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Pablo V. Victoria, research technician II Osmundo C. Bondad, research technician I Pablo S. Lucillo, research technician I Carmelito S. Oca, research technician I Loreto P. Quilantang, research technician I Ariston V. Reyes, research technician I Isidro M. Tolentino, research technician I Efren J. Turla, research technician I

Entomology and Plant Pathology
Twng-Wah Mew, PhD, plant pathologist and head Ossmat Azzam, PhD, virologist1 Michael Benjamin Cohen, PhD, entomologist Kong Luen Heong, PhD, entomologist Hei Leung, PhD, plant pathologist Kenneth G. Schoenly, PhD, insect ecologist1 Jatinder Kumar, PhD, visiting scientist1 Christopher Mundt, PhD, visiting scientist Serge Savary, PhD, visiting scientist1, consultant4 Ram Sharma, PhD, visiting scientist1 Jan E. Leach, PhD, adjunct scientist Laetitia Willocquet, PhD, IRS seconded from IRD1 James C. Correll, PhD, visiting scientist3 Georges M. Reversat, PhD, IRS seconded from IRD4 Lene Sigsgaard, PhD, collaborative scientist Robert S. Zeigler, PhD, consultant3 Casiana M. Vera Cruz, PhD, consultant Michael J. Way, PhD, consultant Jagadish S. Bentur, PhD, consultant3 Edwin Alcantara, PhD, consultant3 Syed Nurul Alam, PhD, consultant3 Bart Cottyn, BS, project scientist Emerlito Borromeo, PhD, consultant3; project scientist4 Ahmed Dirie, PhD, project scientist Chen Baotang, PhD, project scientist1 Elsa Rubia-Sanchez, PhD, project scientist4 Pompe Sta. Cruz, PhD, project scientist1 Tan Wanzhong, PhD, project scientist Wang Zonghua, PhD, project scientist1 Wu Changjian, PhD, project scientist1 Yu Xiao Ping, PhD, project scientist Zheng Rong Zhu, PhD, project scientist4 Zhang Wenjun, PhD, project scientist Hong-Sik Shim, collaborative research fellow3 Yu Xuefang, collaborative research fellow3 Jae-Hwan Roh, MS, collaborative scientist1 Alberto T. Barrion, MS, senior associate scientist Pepito Q. Cabauatan, PhD, senior associate scientist Francisco A. Elazegui, MS, senior associate scientist Remedios M. Aguda, MS, assistant scientist II Marietta R. Baraoidan, MS, assistant scientist II Marichu A. Bernardo, MS, assistant scientist II Alicia A. Bordeos, MS, assistant scientist II Rogelio C. Cabunagan, MS, assistant scientist II Isaias T. Domingo, BS, assistant scientist II

Isabelita P. Ona, MS, assistant scientist II Imelda Rizalina S. Soriano, MS, assistant scientist II Filomena C. Sta. Cruz, MS, assistant scientist II Liberty Almazan, BS, assistant scientist I Helen A. Barrios, BS, assistant scientist I Nancy P. Castilla, PhD, assistant scientist I Josie Lynn A. Catindig, MS, assistant scientist 14 Gilda J. Miranda, MS, assistant scientist I2 Raymond S. Pamplona, BS, assistant scientist I Ma. Angeles Quilloy, MS, assistant scientist I Imelda Revilla, MS, assistant scientist I Angelina M. Romena, MS, assistant scientist I Lourdes M. Sunio, BS, assistant scientist I Allan D. Velilla, MS, assistant scientist I Carmencita C. Bernal, BS, researcher Edgardo L. Coloquio, BS, researcher Luzviminda R. Fernandez, BS, researcher Judy O. Manalo, BS, researcher Anna Cecilia Millena, MS, researcher1 Ma. Reina Suzette B. Madamba, MS, researcher4 Lorna Nieva, BS, researcher Marilou Ramos, BS, researcher Ellen S. Regalado, researcher5 Veritas Morena Salazar, BS, researcher Jesselle L. Solivas, BS, researcher3 Liza Farah Tisalona, BS, researcher Kathryn Umadhay, BS, researcher1 Sylvia C. Villareal, BS, researcher Maria Ymber Villamayor, BS, researcher Maria Leonora M. Yambao, BS, researcher2 Paulina M. Roxas, BS, administrative coordinator Nonnie P. Bunyi, BS, secretary II Crisanta G. Culala, BS, secretary II Elena G. Genil, BS, secretary II Josefina Y. Mata, BS, secretary II Cecilia L. Salonga, BS, secretary II Maria Virlina Casañas, secretary I1 Noel L. Sosa, office clerk Epifania F. Garcia, lead research technician III Elenita T. Silab, lead research technician III Leonido M. Angeles, research technician III Timoteo D. Aranzaso, Jr., research technician III Esquirion A. Baguioso, research technician III Florencio R. Balenson, research technician III Maximino G. Banasihan, research technician III Conrado P. Bandian, research technician III Ernesto M. Camangon, research technician III Benedicto H. Consignado, research technician III Lilibeth F. Datoon, research technician III Noriel P. Deomano, research technician III Panfilo T. Domingo, Jr., research technician III Ponciano H. Edeza, research technician III Fernando V. Elec, research technician III Mario R. Izon, research technician III Armando C. Iranzo, research technician III Glicerio M. Javier, research technician III5 Hernando A. Jordan, research technician III Wilfredo M. Lanip, research technician III Eufrocino M. Pizarra, research technician III

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Celso L. Lantican, research technician III5 Flavio A. Maghirang, research technician III Levorio G. Pamulaklakin, research technician III Eufrocino M. Pizarra, research technician III Alexander G. Ramos, research technician III Pedro F. Reaño, research technician III Errol T. Rico, research technician III Romulo B. Sernadilla, Sr., research technician III Danilo D. Vasquez, research technician III Sergio G. Velasco, research technician III Rodante R. Abas, research technician II Ruben C. Abuyo, research technician II Nestor M. Amoloza, research technician II Modesto A. Calica, research technician II Crispulo B. Cura, research technician II5 Deomedes M. Dizon, research technician II Danilo A. Gonzales, research technician II5 Tomas S. Llaneta, research technician II Nicanor D. Lobos, research technician II5 Clemencio A. Mamiit, research technician II Leovino B. Matundan, research technician II Alberto L. Naredo, research technician II Reyuel C. Quintana, research technician II Noel L. Salac, research technician II5 Juan B. Reyes, research technician II Venancio M. Reyes, research technician II Antonio M. Salamatin, research technician II

Plant Breeding, Genetics, and Biochemistry
Gurdev S. Khush, PhD, principal plant breeder and head Sant S. Virmani, PhD, plant breeder John Bennett, PhD, senior molecular biologist Darshan S. Brar, PhD, plant breeder Zhikang Li, PhD, plant molecular geneticist Surapong Sarkarung, PhD, plant breeder Swapan K. Datta, PhD, plant biotechnologist Karabi Datta, PhD, plant biotechnologist Brigitte Courtois, PhD, IRS seconded from CIRAD-CA1 Moon Hee Lee, PhD, IRS seconded from RDA-Korea Hiroshi Kato, PhD, plant breeder1 Yoshimichi Fukuta, PhD, plant breeder4 Erik Sacks, PhD, affiliate scientist4 Kenneth McNally, PhD, affiliate scientist Parminder S. Virk, PhD, affiliate scientist4 Dong Hee Chung, PhD, visiting scientist1 Sanjay Katiyar, PhD, visiting scientist Kapil Deo N. Singh, PhD, visiting scientist1 Li Xiaofang, MS, visiting scientist3 Lijun Luo, PhD, visiting scientist3 Ghorban Ali Nematzadeh, PhD, visiting scientist1 M. Ilyas Ahmed, PhD, project scientist Navtej S. Bains, PhD, project scientist Glenn Gregorio, PhD, project scientist1 Kyu-Seong Lee, PhD, project scientist Sabaraniappan Robin, PhD, project scientist Alma Sanchez, PhD, project scientist

Hiroshi Tsunematsu, PhD, project scientist1; consultant4 Jumin Tu, PhD, project scientist Lishuang Shen, PhD, project scientist1 Bie Xuezhi, PhD, project scientist Yu Sibin, PhD, project scientist1 Rajendra P. Kaushik, PhD, project scientist Arumugam Kathiresan, PhD, project scientist Sanjay Singh, PhD, project scientist4 Jagdir S. Sidhu, PhD, project scientist4 Weijun Xu, PhD, project scientist4 Enrique R. Angeles, PhD, consultant Corazon Menguito, PhD, consultant3 Suvit Pushpavesa, PhD, consultant3 Aleli Vasquez, BS, consultant1 Georgina Vergara, MS, consultant1 Ellen Tumimbang, MS, consultant4 Yunzhu Jiang, BS, consultant3 E.A. Siddiq, MS, consultant3 Moon-Lee Baek, PhD, collaborative research fellow3 Mun-Sik Shin, PhD, collaborative research fellow4 Louise Friis Bach Jensen, MS, collaborative research fellow Junjian Ni, PhD, collaborative research fellow3 Akifumi Shimizu, collaborative research fellow3 Bo-Kyeong Kim, PhD, collaborative research fellow4 Hyun Soon Kim, collaborative research fellow3 Young-Seop Shin, collaborative research fellow1 Jong-Rae Kang, collaborative research fellow1 Am Farouk, collaborative research fellow3 Normita M. dela Cruz, MS, senior associate scientist Jose C. de Jesus, MS, assistant scientist II Antonio A. Evangelista, BS, assistant scientist II Alvaro M. Pamplona, BS, assistant scientist II Rodolfo S. Toledo, MS, assistant scientist II Editha M. Abrigo, BS, assistant scientist I Modesto M. Amante, MS, assistant scientist I Mark Dondi Arboleda, MS, assistant scientist I7 Carlos L. Casal, Jr., BS, assistant scientist I Julio Chavez, BS, assistant scientist I5 Susan V. Constantino, BS, assistant scientist I Leodegario A. Ebron, MS, assistant scientist I5 Marcelino A. Laza, BS, assistant scientist I5 Norvie L. Manigbas, MS, assistant scientist I2 Ruth E. McNally, MS, assistant scientist I5 Rhulyx O. Mendoza, BS, assistant scientist I Norman P. Oliva, MS, assistant scientist I Robert C. Ona, BS, assistant scientist I Adoracion P. Resurreccion, MS, assistant scientist I Jessica D. Rey, MS, assistant scientist I Benito U. Romena, BS, assistant scientist I Lina B. Torrizo, MS, assistant scientist I Dante Adorada, MS, assistant scientist I4 Mary Jeannie Yanoria, BS, assistant scientist I5 Catharine A. Aquino, BS, researcher5 Elmer V. Aquino, BS, researcher5 Justina M. De Palma, BS, researcher5

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Reycel M. Maghirang, MS, researcher5 Doris M. Mercado, BS, researcher5 Joie A. Molinawe, BS, researcher5 Apollo Neil R. Monroy, BS, researcher5 Mark Tamerlane S. Nas, BS, researcher4,5 Eric L. Paragas, BS, researcher5 Jose P. Roxas, MS, researcher5 Darlene L. Sanchez, BS, researcher5 Jason D. Talag, BS, researcher5 Ma. Theresa G. Sta. Cruz, BS, researcher5 Rosalie E. Lanceras, BS, researcher Hilario Farcon, database administrator II4 Elma N. Nicolas, BS, administrative coordinator Leonida P. Nazarea, BS, secretary II Yolanda C. Aranguren, BS, secretary II5 Minerva B. Bandian, BS, secretary II Nelie M. delos Reyes, BS, secretary II Florie Hernandez, BS, secretary II Emily P. Alcantara, BS, secretary I5 Lorelie S. Olivo, BS, secretary I5 Michelle H. Viray, BS, secretary I5 Leonardo S. Estenor, BS, lead research technician Blesilda G. Albano, BS, research technician III Danilo B. Balagtas, research technician III Socorro Carandang, BS, research technician III5 Danilo C. de Ocampo, research technician III Mario M. Escote, research technician III5 Melquiades G. Evangelista, research technician III Angelito S. Francisco, research technician III Reynaldo P. Garcia, research technician III German T. Jara, research technician III Roberto G. Marasigan, research technician III Joselito U. Oboza, research technician III Inofra I. Sandoval, BS, research technician III Alfredo L. Tandingan, research technician III Jonathan R. Abengania, BS, research technician II Emmanuel R. Adique, research technician II5 Juan L. Alzona, research technician II5 William D. Angeles, research technician II5 Virgilio M. Angeles, research technician II Gener P. Aquino, research technician II Renel C. Aventurado, research technician II5 Victor P. Banasihan, research technician II4,5 Ma. Gina L. Borja, research technician II4,5 Joselito M. Calibo, research technician II Luisito L. Caracuel, research technician II Ronaldo L.Cornista, research technician II5 Marifa L. Corral, BS, research technician II5 Reynaldo J. dela Cueva, research technician II5 Imelda V. Galang, research technician II5 Mario A. Garcia, research technician II5 Oscar A. Gonzales, research technician II Francisco V. Gulay, research technician II Cenon L. Lanao, research technician II5 Noel P. Llanza, research technician II5 Mario A. Lapiz, research technician II Evelyn A. Liwanag, research technician II5 Orlando T. Lucero, research technician II Carmela D. Malabanan, research technician II5 Noel S. Malabanan, research technician II4,5

Eduardo T. Managat, research technician II5 Eleazar O. Manalaysay, research technician II5 Alejandro C. Manio, research technician II Marina C. Manzanilla, BS, research technician II5 Josefina G. Mendoza, research technician II5 Virginia P. Meulio, research technician II5 Florencia A. Montecillo, research technician II5 Arsenio R. Morales, research technician II Joselito Panting, research technician II Daniel L. Pasuquin, research technician II Juanito M. Pasuquin, research technician II5 Macario S. Perez, Sr. research technician II Norberto T. Quilloy, research technician II5 Nestor D. Ramos, research technician II Carlos L. Rosales, research technician II5 Rosalio L. Rosario, research technician II5 Julito P. Talay, research technician II Gil T. Tamisin, research technician II Irma R. Tamisin, research technician II Noe Zarate, research technician II1,5 Teodoro L. Atienza, research technician I5 Patricio Carandang, research technician I5 Mario B. Corral, research technician I5 Rodante Nuevo, research technician I5 Allan Trinidad, research technician I5

Social Sciences
Mahabub Hossain, PhD, economist and head and interim Deputy DDG-R from April 1999 David Dawe, PhD, agricultural economist Sushil Pandey, PhD, agricultural economist (and acting head from April 1999) Kam Suan Pheng, PhD, GIS specialist Mercedita A. Sombilla, PhD, affiliate scientist, policy economist and acting head, LCP Stephen R. Morin, PhD, anthropologist8 Christopher Edmonds, PhD, affiliate scientist Thi Ut Tran, PhD, consultant3 Abedullah, PhD, consultant3 Bao Giang Chau Nguyen, consultant4 Tim J. Coelli, PhD, consultant3 Lay Cheng Tan, consultant-editor1 Abdul Baten, consultant3 Maria S. Floro, PhD, consultant3 Douglas Gollin, PhD, consultant3 Karen McAllister, MES, collaborative research fellow4 Cyril Alther, MA, collaborative research fellow1 Timm Blohm, collaborative research fellow1 Diemuth Pemsl, collaborative research fellow1 Ho Cao Viet, collaborative research fellow3 Manik Lal Bose, MS, consultant4 Thomas Oberthur, PhD, consultant3 Do Minh Phuong, consultant3 Pieternella Maria Bolink, consultant1 Hum Nath Bhandari, PhD, consultant4 Gana P. Ojha, PhD, consultant4 Yujiro Hayami, PhD, visiting scientist3 Masao Kikuchi, PhD, visiting scientist3

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Lisa M.L. Price, PhD, visiting scientist3 Suresh Pal, PhD, visiting scientist3 Chu Thai Hoanh, PhD, project scientist1; affiliate scientist4 Thelma R. Paris, MS, affiliate scientist gender specialist Esteban C. Godilano, PhD, project scientist4 Nguyen Tri Khiem, PhD, project scientist Aldas Janaiah, PhD, project scientist4 Piedad F. Moya, MS, senior associate scientist Florencia G. Palis, MS, assistant scientist2 Catalina P. Diaz, MS, assistant scientist Fe B. Gascon, MS, assistant scientist Joyce S. Luis, MS, assistant scientist Maritess M. Tiongco, MS, assistant scientist Lourdes E. Velasco, MS, assistant scientist Renato Villano, BS, assistant scientist Nestor G. Fabellar, BS, database administrator Don Pabale, BS, database administrator Josephine H. Narciso, BS, database administrator Aileen Alvaran, BS, researcher Sharon Fajardo, MS, researcher Esther B. Marciano, BS, researcher Ellanie R. Cabrera, BS, researcher5 Pio Adan A. Cenas, BS, researcher Melina Magsumbol, BS, researcher1 Aida M. Papag, BS, researcher Arnel Rala, BS, researcher Ma. Shiela Valencia, BS, researcher Jose Paul Reyes, BS, system analyst/programmer3 Lorena Villano, BS, programmer Mirla Domingo, BS, administrative coordinator Lydia Damian, BS, senior secretary Rosendo Gutierrez, BS, secretary Shirley Raymundo, BS, secretary Nancy Palma, BS, lead research technician Frederick Lagasca, BS, statistical assistant Teodora Malabanan, BS, statistical assistant Joel Reaño, BS, statistical assistant Cornelia Alforja, BS, graphics assistant

Soil and Water Sciences
Guy Joseph Dunn Kirk, PhD, soil chemist and head Jagdish K. Ladha, PhD, soil nutritionist To Phuc Tuong, PhD, water management engineer Bas Bouman, PhD, water scientist4 Wolfgang Reichardt, PhD, microbiologist Reiner Wassmann, PhD, IRS seconded from Fraunhofer Institute for Atmospheric Environmental Research1 Achim Dobermann, PhD, soil nutrient specialist P.M. Reddy, PhD, affiliate scientist4 Jonathan Arah, PhD, IRS seconded from the Institute of Terrestrial Ecology John L. Gaunt, PhD, IRS seconded from the Institute of Arable Crops Research Pongmanee Thongbai, PhD, project scientist1 Haishun Yang, PhD, project scientist Milkha Aulakh, PhD, project scientist1

Gyaneshwar Prasad, PhD, project scientist Christian Witt, PhD, project scientist1 Xuan Hien Nguyen, consultant3 Euan Kevin James, PhD, consultant3 Yahai Lu, PhD, consultant3 Nguyen Van Ngoc, consultant3 A.R. Pal, PhD, consultant3 Himanshu Pathak, PhD, consultant4 Gary Stacey, PhD, visiting scientist3 Jatish Chandra Biswas, PhD, consultant1 Maddala V.R. Murty, PhD, consultant1 Md. Murshedul Alam, PhD, consultant1 Subhash Chandra Verma, collaborative research fellow3 Susana Bucher, collaborative research fellow1 Rhoda S. Lantin, MS, senior associate scientist Corinta Q. Guerta, MS, senior associate scientist Domingo F. Tabbal, MS, senior associate scientist Leandro V. Buendia, MS, assistant scientist II1 Agnes T. Padre, MS, assistant scientist II Gregorio Simbahan, BS, assistant scientist II Mirasol F. Pampolino, MS, senior research assistant2 Ma. Carmelita R. Alberto, MS, assistant scientist I Jocelyn B. Aduna, BS, assistant scientist I Anita A. Boling, MS, assistant scientist I Romeo J. Cabangon, MS, assistant scientist I Ambrocio R. Castañeda, BS, assistant scientist I Rubenito M. Lampayan, MS, senior research assistant2 Rolando B. So, MS, assistant scientist I Teresita S. Ventura, BS, assistant scientist I Aurelio Briones, Jr., MS, assistant scientist I2 Ma. Arlene A. Adviento, MS, assistant scientist I5 Ernesto Castillo, MS, assistant scientist I Alona Umali, BS, assistant scientist I1 Ruthchelle de Jesus, BS, assistant scientist I Estela Pasuquin, MS, assistant scientist I Olivyn Angeles, MS, assistant scientist I Evelyn Belleza, BS, researcher Maribeth Zarate, MS, researcher5 Liza Lubigan, BS, researcher1 Rowena H. Oane, BS, researcher Jocelyn Uichanco, BS, researcher Gloria Gamat, BS, researcher Wenceslao Larazo, BS, researcher5 Crisanta Bueno, BS, researcher Joy Guingab, BS, researcher4 Jhenny Flor Galan, BS, researcher4 Elisa M. Tabaquero, BS, administrative coordinator Lourdes Herrero, BS, secretary II Lolita Adriano, BS, secretary II Florencia Junsay, BS, secretary II Mary Ann Burac, BS, data encoder5 Lizzida Pantaleon, BS, data encoder5 Maximo Alumaga, lead research technician Rene Carandang, AB, research technician III Pedro Malabuyoc, research technician III Enrique Reyes, research technician III Lucio Caramihan, research technician III

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Rollin de Ocampo, BS, research technician III5 Juanito Fortuna, research technician III Eduardo Tandang, research technician III Manolito Victoria, research technician III Briccio Salisi, research technician III Ricardo Eugenio, research technician III Dunstan Tito Ople, research technician II5 Jerone Onoya, research technician II Ananias Magbanua, Jr., research technician II1 Andrew Revilleza, research technician II5 Alfredo Barlan, Jr, research technician II1 Nilo Driz, research technician II Graciana Clave, BS, research technician II5 Ferdinand Corcuera, research technician II Feriano Javier, research technician II Andres Lawas, research technician II1 Sonny Pantoja, research technician II1 Angel Bautista, research technician I5 Juanito Florentino, research technician I5

Experiment Station
Mark A. Bell, PhD, head George F. Pateña, MS, manager2 Tomas P. Clemeno, MS, manager Arnold R. Manza, MS, manager Loreto B. Aclan, BS, ES supervisor II Bienvenido B. Manimtim, BS, ES supervisor II Vivencio P. Marciano, BS, ES supervisor II Erlinda A. Oracion, BS, administrative coordinator Roberto P. Escandor, BS, ES supervisor I Lauro R. Malihan, AB, ES supervisor I Mario A. Mandilag, Sr., ES supervisor I Apolinario B. Resurreccion, ES supervisor I Candido S. Solivas, BS, lead research technician Isaias C. Abuyo, AB, lead research technician Jose D. Manuel, BS, lead research technician Celso L. Varron, lead research technician Jose H. Sacdalan, lead research technician Rolando D. Llorico, lead research technician Napoleon C. Calatraba, lead research technician Sulpicio J. Malabanan, lead research technician Valentin C. Burgos, lead research technician Nazario B. Timbol, lead research technician Paul M. Sarmiento, programmer Manuel B. Demontano, equipment operator II Jose F. Hernandez, equipment operator II Nicasio V. Malabanan, equipment operator II Leopoldo J. Mercado, equipment operator II Marcial E. Pabalate, equipment operator II Democrito A. Puma, equipment operator II Francisco G. Calibo, equipment operator I Edgardo B. Pamulaklakin, equipment operator I Marcelo P. Torres, equipment operator I Luzvimindo L. Mapiscay, electrician I Rolando G. Guevarra, mechanic II Rogelio R. Pamulaklakin, mechanic II Juanito M. Rosario, mechanic II Efren E. Viquiera, mechanic II Romeo T. Llamas, welder

Virginia G. Aranda, BS, secretary II Enrico A. Lucero, secretary II Cecilio L. Villamayor, secterary I Jesse C. Banasihan, warehouseman Rolando R. Esguerra, BS, stock assistant Rolando R. Pacion, stock assistant Ricardo C. Sioson, office clerk Abraham G. Dalid, AB, research technician III Sabino M. Parducho, research technician III Eleuterio M. Alanguilan, BS, research technician II Pedro C. Aala, research technician II Efren A. Bagui, research technician II Luis M. Calma, research technician II Aurelio M. Catangay, research technician II Gaudencio S. Indico, research technician II Rogelio M. Elbo, research technician II Pedro A. Maghirang, research technician II Pedro C. Mendoza, research technician II Ramiro C. Panting, research technician II Reynaldo A. Pelegrina, research technician II Godofredo E. Ramos, research technician II Roberto B. Revilleza, research technician II Nestor G. Rizaldo, research technician II Efren L. Blanco, research technician II Cesar Z. Esguerra, research technician II Benjamin C. Garcia, research technician II Andres M. Mercado, research technician II Fabian L. Alcachupas, research technician II Nestor M. Angeles, research technician II Severo B. Bonsol, research technician II William C. Fortuna, research technician II Vicente E. Carandang, research technician II Virgilio T. Lalap, research technician II Marcelino O. Magpantay, research technician II Leopoldo P. Manito, research technician II Antonio B. Rivera, research technician II Pablito M. Pabalate, research technician II Daniel A. Barrion, research technician II Delfin M. Ilagan, research technician II Eduardo A. Lajarca, research technician II Danilo O. Amoloza, research technician II Godofredo M. Mercado, research technician II Restituto M. Bandoy, research technician II Pedro C. Cabrera, Sr., research technician II Abraham G. Javier, research technician II Gregorio S. Oca, research technician II Melecio J. Arcillas, research technician II Oscar L. Caspillo, research technician II Ariel R. Dimapilis, research technician II Rogelio V. Bargola, research technician II Danilo O. Gonzaga, research technician II Nestor L. Ilaw, research technician II Fidel G. Lanorio, research technician II Carlos P. Alforja, research technician II Mateo F. Manzanilla, research technician I Quirino L. Atienza, research technician I Lino M. Carandang, research technician I Bonifacio B. de Chavez, research technician I Lucas M. Malbataan, research technician I Mario M. Malbataan, research technician I

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Gelardo R. Morales, research technician I

Seed Health Unit
Twng-Wah Mew, PhD, plant pathologist and head Silvino D. Merca, MS, assistant scientist II Patria G. Gonzales, MS, assistant scientist II Carlos C. Huelma, BS, assistant scientist I Jocelyn O. Guevarra, BS, researcher Evangeline G. Gonzales, BS, secretary I Isabel L. Penales, research technician III Pedro E. Aquino, BS, research assistant III Gertrudo R. Arcillas, research technician III Atanacio B. Orence, research technician III Florencio Lapiz, research technician II4 Jose Banasihan, research technician I4 Aurelio Gamba, research technician I4 Salome Palmones, data encoder4

Biometrics Unit
Cristopher Graham McLaren, PhD, biometrician and head Violeta I. Bartolome, MOS, statistical specialist Rolando M. Casumpang, BS, systems analyst/ programmer Aleli B. Olea, MS, training specialist1 Maria Isabel Ferino, MS, training specialist4 Maria Cristina Jawili, MS, assistant scientist4 Lanie C. Quintana, MS, assistant scientist I1 Criselda G. Ramos, BS, researcher Arllet M. Portugal, MS, database administrator II Luralyn M. Ramos, BS, database administrator II Lourdes C. Paunlagui, BS, administrative coordinator William Eusebio, IT technician

Analytical Service Laboratories
Bernardita E. Mandac, MS, assistant scientist II Rosario R. Jimenez, BS, assistant scientist I Joselito T. Guyo, BS, instrumentation specialist Lilia R. Molina, BS, researcher Ma. Carmela Ong, BS, research assistant4 Aniceto B. Boncajes, BS, research technician III Rufino D. Manuel, research technician III Jose G. Rosales, research technician III Edgar O. Amoloza, research technician III Jesus S. Belen, research technician III Ruben G. Chavez, ASL supervisor I

Genetic Resources Center
Michael T. Jackson, PhD, head and germplasm specialist Sang-Won Ahn, PhD, plant pathologist and acting INGER coordinator1 Edwin L. Javier, PhD, INGER coordinator4 Bao-Rong Lu, PhD, germplasm specialist

Jean-Louis Pham, PhD, population geneticist, IRS seconded from IRD Genoveva C. Loresto, MS, project scientist5 S. Appa Rao, PhD, project scientist based in Lao PDR5 Flora C. de Guzman, MS, senior associate scientist Renato A. Reaño, MS, assistant scientist II Ma. Concepcion U. Toledo, BS, assistant scientist II Ma. Socorro R. Almazan, BS, assistant scientist I Amita B. Juliano, BS, assistant scientist I Ma. Elizabeth B. Naredo, BS, assistant scientist I Adelaida P. Alcantara, BS, database administrator II Evangeline B. Guevarra, AB, database administrator II Victoria C. Lopez, BS, database administrator II Zenaida M. Federico, BS, administrative coordinator Marlon A. Calibo, BS, GRC supervisor I5 Sheila Mae E. Quilloy, BS, researcher5 Marilyn G. Belen, AB, researcher5 Jose L. Angeles, BS, lead research technician Minerva I. Macatangay, lead research technician Bernardo P. Mercado, lead research technician Bernardino T. Almazan, research technician III Virgilio T. Ancheta, research technician III Vicente A. Arcillas, research technician III Emerlinda E. Hernandez, research technician III Felix R. Llanes, research technician III Virgilio P. Magat, research technician III Gregorio M. Mercado, research technician III Mario A. Rodriguez, research technician III Ernesto C. Sumague, research technician III Mila D. Obligado, secretary II Digna I. Salisi, BS, secretary II Teresita C. Santos, AB, secretary II Ma. Concepcion Lotho, BS, data encoder4 Remigio L. Aguilar, research technician II Nelia D. Angeles, BS, research technician II Noel R. Banzuela, research technician II Hipolito M. Elec, research technician II1,5 Rolando V. Evangelista, research technician II Arnold B. Gonzales, research technician II Nestor P. Leron, research technician II Jose M. Marasigan, research technician II Honorio M. Oboza, research technician II Renato T. Pizon, research technician II Romulo R. Quilantang, research technician II Florencio F. Villegas, research technician II Melencio R. Lalap, office clerk Lydia G. Angeles, BS, research technician I5 Imelda P. Boncajes, research technician I5 Ma. Sarah Q. Cabungcal, research technician I1,5 Isabelita P. de Mesa, BS, research technician I5 Minerva N. Eloria, AB, research technician I5 Alicia A. Lapis, BS, research technician I5 Wilma L. Lumaybay, research technician I5 Yolanda P. Malatag, AB, research technician I5

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Veronica V. Mangubat, research technician I5 Violeta T. Manila, research technician I1,5 Jacqueline D. Manuel, research technician I5 Maridee Pontipedra, research technician I4

Information Center
Ian Wallace, MLS, librarian and head and interim director for administration and human resources Eugene P. Hettel, MA, science editor and CPS head and interim head, IC Bill Hardy, PhD, science editor/publisher Carolyn Dedolph, MS, consultant1 Walter G. Rockwood, MS, consultant3 Barbara Richards, MA, consultant1 Mila M. Ramos, MLS, assistant librarian and acting head, Library and Documentation Services Mario M. Movillon, MS, manager Carmelita S. Austria, MLS, assistant librarian Sylvia Katherine S. Lopez, MS, assistant manager II Albert A. Borrero, CPS assistant manager II Teresita V. Rola, BS, CPS assistant manager I Ginalyn H. Santos, BS, web developer and multimedia designer4 Manuel S. Alejar, MM, VECS supervisor II Teofila E. Barcenas, MLS, collections development librarian1 Editha S. Lantican, MLS, rice bibliographer Iris Marigold P. Operario, BLS, collections development librarian4 Antonette Abigail E. Caballero, MBA, administrative coordinator Estrella Castro, BS, administrative coordinator Kazuko Morooka, BA, librarian (Japan Library Office) John Cedric O. Nepomuceno, BS, video writer/ producer4 Melita Q. Magsino, AB, CPS supervisor I Eva B. Ramin, BS, CPS supervisor I Rogelio M. Alfonso, CPS supervisor I Erlie E. Putungan, BS, graphics designer Juan V. Lazaro IV, graphics designer Grant L. Leceta, graphics designer Emmanuel A. Panisales, BS, graphics designer Raul S. Ramiro, Jr., graphics designer1 Lingkod C. Sayo, BS, photographer Bartolome B. Vibal, photographer Rodolfo L. Carpio, video specialist Jose M. Ibabao, audiovisual technician II Zorayda T. Menguito, VECS assistant Arvin A. Benavente, BS, audiovisual technician Reynaldo G. Patulot, office clerk Lorenzo C. Santos, BS, marketing assistant Natalia V. delos Reyes, BS, IT technician Isagani P. Garcia, library assistant Francisco A. Jaraplasan, library assistant Mauro T. Malabrigo, Jr., library assistant Emmanuel P. Mendoza, BS, library assistant Charlene R. Ramos, BS, library assistant Guido O. Talabis, library assistant Corvette M. Apolinario, library assistant

Reynaldo L. Stevens, printer Harris L. Tumawis, Riceworld assistant Romeo R. Dimapilis, BS, sales assistant Rogelio R. Quintos, BS, secretary II Susan A. Robles, BS, secretary I Cynthia C. Quintos, BS, secretary I George R. Reyes, BS, secretary I Arleen A. Rivera, office clerk

Computer Services
Paul O’Nolan, MS, IT manager Kishore Bhargava, consultant3 Peter Ditoto, BS, consultant3 Rogelio Alvarez, Jr., BS, CS assistant manager II Joel E. Macatangay, BS, CS assistant manager II Wenceslao C. Alimagno, BS, CS supervisor II Ma. Christina M. Abuan, BS, systems analyst/ programmer Alexander B. Cosico, BS, systems analyst/ programmer Ildefonso B. Cosico, AB, systems administrator Arturo L. Gonzales, BS, computer technician Marlene M. Chang, computer technician Bayani N. Perido, computer technician

Training Center
Robert T. Raab, PhD, acting head1 Gana Pathi Oja, PhD, consultant4 Carrie Lee Chung, MA, consultant3 Douglas James Gray, PhD, consultant3 Shah Faisal, consultant3 Chung Jun-Yong, collaborative research fellow3 Madeline B. Quiamco, PhD, TC assistant manager Oscar A. Garcia, BS, training specialist Rogelio T. Rosales, MS, training specialist Buenafe R. Abdon, BS, training assistant1 Sylvia P. Avance, BS, training assistant Ma. Teresa A. Clabita, BFA, training assistant Gina E. Zarsadias, MM, training assistant Irvin M. Panganiban, BS, training assistant Rina P. Coloquio, BS, secretary II Lorenzo D. Ocampo, Jr., BS, secretary I Macario B. Montecillo, training logistics assistant

International Programs Management Office
Headquarters-based Vethaiya Balasubramanian, PhD, agronomist/ CREMNET coordinator Werner Stür, PhD, CIAT forage agronomist (affiliate scientist) Subbiah Elangovan, PhD, economist/CREMNET project scientist3 Ma. Victoria O. Espaldon, PhD, consultant (Bhutan)3 Julian A. Lapitan, MS, senior associate scientist Abraham M. Mandac, MS, assistant scientist II Antonio C. Morales, MS, assistant scientist II

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Francisco G. Gabunada, Jr., BS, assistant scientist I Emma Luisa A. Orencia, BS, researcher Alberto M. Aguilar, BS, administrative coordinator Ma. Diadema G. Bonilla, BS, administrative coordinator Margaret Ann S. Jingco, BS, administrative coordinator Felicidad S. Danglay, BS, secretary II Ruperto D. Torres, BS, research technician III Leonida F. Angeles, research technician II Dominador A. Calica, research technician II

Pen Saim Il, guard Phon Chanthea, guard Ros Savuth, guard Seng Saran, guard Suen Sothy, guard Yong Savoeun, guard

Outposted staff
Bangladesh Sadiqul I. Bhuiyan, PhD, IRRI representative for Bangladesh and water scientist Noel P. Magor, PhD, project manager, PETRRA Project4 Jill Lenne, PhD, consultant3 M. Suyajet U. Chowdhury, PhD, consultant3 Salauddin Ahmad, MS, PETRRA project officer4 Salim Ahmed, BA, senior administrative officer Jamila Khandekar, BS, administrative officer Manik Lal Bose, MS, GIS consultant A.K.M. Azad Chowdhury, BS, research/ administrative assistant Mohamad Samad, office attendant Mohammad Jamal, driver M. Ahsanullah, driver Mohammad Naseem, driver M. Abdul Majid, gardener M. Alimullah, guard Fazlu Miah, guard Cambodia Harry J. Nesbitt, PhD, agronomist and team leader Peter G. Cox, PhD, agricultural economist Gary C. Jahn, PhD, crop protection specialist Joseph F. Rickman, MS, agricultural engineer Peter F. White, Ph D, soil scientist1 Lorelei Domingo, BS, administrative assistant/ cashier Toun Srey, office helper Huy Lisa, driver Kry Lak, driver Ouk Samnang, driver Phon Leang An, driver Ros Sarun, driver Sim Kim Chan, driver Hul Choeun, guard Im Thay, guard Ek Sokhim, guard4 Kan Kong, guard1 Khim Nat, guard Men Sothea, guard Nou Sokhom, guard Ou Bora, guard

Consultants Candelaria Tolentino, BS, English as a Second Language3 Kate Roberts, evaluation framework3 Iean Russels, evaluation framework3 Keith Milligan, organizational structure3 Luke Leung, PhD, rat control3 Seconded from the Ministry of Agriculture, Forestry, and Fisheries Ros Chhay, PhD, soil scientist Mak Solieng, PhD, social scientist Men Sarom, PhD, plant breeder Chan Phaloeun, MS, farming systems agronomist Chea Sareth, BS, farming systems assistant Chhorn Nel, BS, crop protection assistant Hun Yadana, BS, plant breeding assistant Kep Poch, BS, farming systems assistant4 Khay Sathya, BS, training assistant4 Khiev Bunnarith, BS, research assistant Khun Leanghak, BS, co-chief of station operations Lang Mondul, BS, training assistant Lor Bunna, BS, glasshouse supervisor Mot Sana, BS, social science assistant4 Pao Sinath, BS, agricultural engineer Pith Khon Hel, BS, plant breeder Pol Chanthy, MS, crop protection assistant Sakhan Sophany, MS, research assistant4 Say Puthea, Dipl., director of station operations Sek Kim Sem, agricultural engineer assistant Seng Vang, MS, soil scientist Sum Bunna, MS, agricultural engineer Suon Vanny, MS, research assistant4 Theng Vuthy, BS, farming systems assistant Ty Channa, MS, head of training Ung Sopheap, BS, co-chief of station operations Kim Rany, administrative assistant Ly Somonea, BS, administrative assistant Sim Theavy, administrative assistant/accountant Sok Songly, administrative assistant Prou Nhet, driver Sam Simeth, driver Teng Touch, driver Thap Sokhun, driver Van Sarom, driver Kong Hun, guard Ouk Samphors, guard Oum Phirun, guard Sok Sovannarith, guard

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China Sheng-Xiang Tang, PhD, liaison scientist for China Zhongqiu Wang, BS, administrative assistant/ accountant Li Ding, BS, secretary/cashier India R.K. Singh, PhD, representative and liaison scientist Jamal Pervez Noor, BCom, finance and administrative officer Tara Chand Dhoundiyal, BS, travel assistant Ruchita Mamgain, BA, secretary Chander Mohan, BCom, clerk/messenger Soban Singh Topwal, driver Raj Kumar, driver P. Prasad, attendant Indonesia/Malaysia/Brunei Darussalam Mahyuddin Syam, MPS, communication specialist and liaison scientist Francisca Herjati, Dipl, executive secretary Bambang Soewilanto, BS, administrative assistant Bambang Winarko, BS, accounting supervisor4 Diah Wurjandari, BS, research assistant Darman, driver Endang Suhendi, driver Japan Tadashi Morinaka, PhD, liaison scientist1 Hiroyuki Hibino, PhD, liaison scientist4 Kazuko Morooka, BA, librarian Lao PDR John M. Schiller, PhD, research programmer and team leader Keith Fahrney, PhD, upland agronomist Bruce A. Linquist, PhD, lowland agronomist S. Appa Rao, PhD, project scientist

Ratsimanosika Alphonse, guard Tombosoa Mamy, guard Rakotoarimanana Jean Jacques, guard Myanmar Arnulfo G. Garcia, PhD, cropping systems agronomist and IRRI representative R.P. Kaushik, PhD, project scientist Yolanda Garcia, PhD, resource economics and natural management consultant3 Maung Maung, BS, administrative assistant/ accountant Ohnmartun, BS, research aide/secretary Saw Alexander, BS, clerk/messenger Myint Soe, driver Thailand Boriboon Somrith, PhD, liaison scientist1 Suvit Pushpavesa, MS, consultant Manoch Kongchum, MS, senior research assistant Jutharat Prayongsap, MS, research assistant Pipat Buntham, BS, research assistant Dome Harnpichitvitaya, MS, research assistant Wipha Charuratna, BS, consultant/accountant Aranya Sapprasert, BS, administrative coordinator Panjama Tasana, accounting assistant Vitchu Chowanapong, BS, bank messenger Laddawan Leelagud, office assistant Phikul Kitprasong, BS, office assistant Amporn Sookyong, maid Charoenchai Morakotkheaw, field assistant Chaiporn Soising, field assistant Chusak Kartipatee, field assistant Pramote Tanupant, field assistant Sompong Pachanapool, field assistant Surat Taweesin, driver/mechanic Thavil Sukrak, driver Vietnam Nguyen Thanh Huyen, BS, administrative officer Nguyen Huu Hai, driver/office assistant

Consultants Gertrudo S. Arida, MS, IPM research3 Armando Jerry Erguiza, MS, farming systems research and farming systems training3 David Swete-Kelly, MS, Project Formulation – Integrated Upland Agricultural Research Project3
Madagascar Martha M. Gaudreau, PhD, cropping systems agronomist and team leader Sinha Amadji Pamphile, MS, consultant Ramaherison Milantonirina Antsa, BS, administrative assistant Randrianarisoa Noromalala, secretary Raheliarimanana Hanitra, secretary (part-time) Randrianasolo Jean, lead driver Ratovosoa Andrianantenaina, driver Ratsiranto Rivo, driver4 Andrianera Lala Yves Rostaing, errand man

Public Awareness
Duncan Macintosh, BS, head4 Olivia Sylvia O. Inciong, MS, manager Juanito S. Goloyugo, MM, public awareness specialist Jesse P. Victolero, BS, public awareness photographer1 Nena Y. Dionson, BS, secretary II

Director General’s Office
Sylvia R. Arellano, BS, DG assistant Nida E. Reyes, BS, executive secretary Maura K. Lago, BS, secretary II Anna Christine A. Doctolero, BS, secretary I Rowena L. Natividad, BS, secretary I

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Office of the Deputy Director General for Research
Violeta G. Cordova, MS, DDG assistant manager Adonna M. Robles, MS, program coordinator Lucia V. Gamel, AB, executive secretary Angelina A. Malabrigo, BS, secretary II

Office of the Deputy Director General for Partnerships
Ramon A. Oliveros, MS, technical assistant9 Alma Bernardo, BS, administrative coordinator10

Liaison, Coordination, and Planning
Mercedita A. Sombilla, PhD, head Marietta D. Nadal, BS, administrative coordinator Remedios T. Vivas, BS, secretary Marisol Camasin, BS, office clerk4

Office of the Director for Administration and Human Resources
Charito G. Medalla, BS, executive secretary Vilma T. Ramos, BS, executive secretary Maria Cristina Sison, MS, orientation assistant4 Selene M. Ocampo, BS, administrative coordinator Nympha G. Chang, BS, administrative coordinator Ma. Liza R. Milante, BS, secretary II Joan L. Belsonda, BS, secretary II Priscilla P. Comia, BS, office clerk Human Resources Fe V. Aglipay, MS, manager Grace L. Reyes, MS, HRD supervisor II Eloisa V. Revilla, BS, psychometrician Jacinta I. Evangelista, HRD training assistant Alfredo R. Reyes, BS, HRD benefits assistant Joselito A. Platon, BS, community relations assistant Aida A. dela Rea, BS, medical technologist Evangeline A. Yecyec, BS, HRD assistant Remedios J. Bondad, BS, HRD assistant Ma. Francisca R. Gallivo, HRD assistant Melanie M. Quinto, HRD assistant Iluminada B. Oleta, BS, secretary II Finance Mario F. Ocampo, MBA, manager Ceres M. Pasamba, BS, manager1 Elisa S. Panes, BS, manager Melba M. Aquino, BS, accounting assistant manager Nestor C. Lapitan, BS, cash assistant manager II Leonisa M. Almendrala, BS, systems supervisor II Leny M. Medenilla, BS, budget supervisor II Eleah R. Lucas, BS, budget supervisor I Rolando T. Ramos, BS, cash supervisor II Julie C. Carreon, BS, cash supervisor II

Imelda S. Silang, BS, accounting supervisor II Miriam M. Telosa, BS, accounting supervisor II Ma. Judy M. Anicete, BS, accountant II Helen R. Aquino, BS, accountant II Gemma N. Corcega, BS, accountant II Vicente E. Ganon, BS, accountant II Rodelita Dollano, BS, accountant II4 Lily R. Go, BS, accountant II Leonor Herradura, BS, accountant II4 Reymunda C. Labuguen, BS, accountant II Nestor Marcelo, Jr., BS, accountant II Florante P. Mondez, BS, accountant II1 Juancho N. Pangilinan, BS, accountant II4 Maricel P. Rosario, BS, accountant II Arsenio L. Valeriano, Jr., BS, accountant II Maria Zenaida V. Borra, BS, accountant I Tricia Marie de la Mar, BS, accountant I3 Christina D. Casanova, BS, accountant I Teresita M. Lalap, BS, accountant I1 Paulito J. Oleta, BS, accountant I Grace P. Pascual, BS, accountant I Mary Grace P. Rayco, BS, accountant I Marilyn Ignacio, data encoder4 Flordeliza Lopez, BS, data encoder4 Malaya Salas, BS, data encoder4 Ma. Theresa M. Sevilla, BS, secretary II Noel T. Lantican, BS, secretary I Rizza A. Escondo, AB, secretary I Vilma C. Maligalig, BS, secretary I Roderick B. Maligalig, BS, secretary I Materials Management Ramon Guevara, MBA, manager Generoso San Felipe, BS, materials assistant manager Felicisimo Kalaw, BS, materials supervisor II Zenaida Belarmino, BS, purchaser Lourdes Belison, BS, purchaser Nerisa Gutierrez, BS, purchaser Luzviminda Oleta, purchaser Concepcion Elybeth Alimario, BS, materials assistant Anatolio Magampon, BS, property disposal assistant Irineo Esguerra, warehouseman Ernesto Nimedez, Jr., AB, warehouseman Jose Sibal, warehouseman Priscilla Cabral, BS, shipping assistant Macario Beato, documentation and materials handling clerk Francisco Quilloy, materials expediter Dionisio Dumlao, MM attendant4 William Estrellado, MM attendant4 Delfin Lacandula, Jr., MM attendant4 Edison Samonte, MM attendant4 Maureen Cabarrubias, data encoder4 Jane Carlos, data encoder4 Anicia Malabanan, data encoder4

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Legal Walfrido E. Gloria, MBA, manager Divina M. Marinay, BS, administrative coordinator Cherryl M. Cruz, BS, secretary II4 Internal Audit Unido C. Telesforo, BS, manager, audit1 Communication Remedios E. Ballesfin, BS, administrative coordinator Angelica P. Valintos, BS, administrative coordinator Wilmer B. Jacob, office clerk Roberto T. Paz, office clerk Louell R. Tanzo, BS, central file assistant4 Felix C. Estipona, Makati office assistant4 Food and Housing Ma. Obdulia B. Jolejole, BS, FHS manager II Leody M. Genil, BS, FHS supervisor II Remedios C. Corral, AB, FHS supervisor I1 Melinda M. Cuyno, BS, FHS supervisor I Aurea A. Delantar, FHS supervisor I Fe C. de Ocampo, BS, food service assistant Ricardo L. Bejosano, Jr., housing attendant Cristina E. Cauntay, housing attendant Irene S. Escoses, housing attendant Laureano M. Escuadra, housing attendant Edgardo S. Estenor, BS, housing attendant Aurelio C. Garcia, housing attendant Rogelio P. Granzore, housing attendant Francisca O. Oro, housing attendant Limberto S. Aldipollo, stock assistant Anselmo R. Reyes, recreation assistant Alfredo Regalado, housing attendant4 Security and Safety Office Glenn A. Enriquez, BS, SSO manager II Warlito C. Mendoza, Sr., AB, security supervisor I Andres V. Mendoza, BS, security supervisor I Bionico R. Malacad, security investigator Salvador T. Zaragosa, Jr., security investigator Antonio N. Gapas, SSO coordinator Crisanto P. Dawinan, BS, nurse William G. Amador, BS, core guard Crisostomo M. dela Rueda, core guard Rodelo M. Empalmado, core guard Pablo C. Erasga, core guard Roberto M. Espinosa, Jr., core guard Juanito C. Exconde, BS, core guard Esteban C. Palis, core guard Macario C. Punzalan, BS, core guard Ernesto S. Regulacion, core guard Transport Office Manuel F. Vergara, BS, manager4 John Arturo M. Aquino, BS, vehicle repair shop supervisor Ariel B. Nuque, BS, MVRS coordinator Nelson C. Tagle, dispatching section supervisor

Reynaldo G. Elmido, MPDS dispatcher Sesinando B. Guerta, MPDS dispatcher Bonifacio M. Palis, MPDS dispatcher Carlito C. Cabral, MPDS assistant Perlita E. Malabayabas, BS, secretary II Jaime D. Atienza, mechanic II Romeo L. Jarmin, mechanic II Armando E. Malveda, mechanic II Roduardo S. Quintos, mechanic II Rolando L. Santos, mechanic II Edwin S. Cabarrubias, mechanic I Roger M. Cuevas, mechanic I Mabini M. Linatoc, mechanic I Ronilo M. Villanueva, BS, mechanic I Danilo G. Abrenilla, driver Crisencio L. Balneg, driver Rolando A. Cabrera, driver Amador L. de Jesus, driver Roberto C. Delgado, driver Rodrigo M. Fule, driver Diosdado D. Mamaril, driver Reynaldo P. Martinez, driver Hernani M. Moreno, driver Eduardo L. Pua, driver Angelito C. Quijano, driver Danilo C. Sanchez, AB, driver Oscar A. Templanza, driver Renato C. Vivas, driver Emilio R. Gonzales, Jr., AC mechanic

Physical Plant
Douglas Avila, BS, manager Alfredo Mazaredo, MS, manager Enrique delos Reyes, BS, manager Alberto Adviento, BS, PP supervisor II Emmanuel Eusebio, BS, PP supervisor II Jaime Fojas, BS, PP supervisor II Fernando Madriaga, BS, PP supervisor II Nestor Malabuyoc, BS, PP supervisor II Nilo Barraquia, BS, PP supervisor I Domingo Escasura, PP supervisor I Jaime Angeles, BS, PP supervisor I Teodoro Carreon, PP supervisor I Crisencio Custodio, PP supervisor I Tiburcio Halili, PP supervisor I Rodolfo Calibo, lead physical plant technician Fidel Alvarez, carpenter Rodrigo Castillo, BS, carpenter Levi Malijan, carpenter Virgilio Verano, carpenter Danilo Banasihan, instrument and telephone technician Marcelino Navasero, Jr., instrument and telephone technician4 Leandro Ortiz, instrument and telephone technician Domingo Ortiz, telephone technician Alex Alumaga, plumber II Regalado Alcachupas, plumber Melencio Tapia, plumber

xxi

Manolo de Guia, refrigeration and AC mechanic Rolando Lapitan, refrigeration and AC mechanic Dionisio Ng, refrigeration and AC mechanic Juancho Petrasanta, refrigeration and AC mechanic Ricardo Tabilangon, refrigeration and AC mechanic Roberto Escueta, BS, electrician II4 Rufino Gibe, electrician II Felix Halili, electrician II Benjamin Libutan, electrician II Sabino Ortiz, electrician II Cesar Padonan, electrician II Rolando Simon, electrician II Marissa Templanza, BS, administrative coordinator Benita M. Pangan, BS, office clerk Larry Salgado, BS, drafting technician Manuel Alforja, welder/tinsmith Apolinario Armia, welder/tinsmith Anito Mabalhin, welder/tinsmith Percival Leon, physical plant assistant Francisco Ador, mason Roberto Tamio, mason Luisito Vitan, painter Fermin Junsay, stock assistant

1Left 2On

during the year. leave. 3Joined and left during the year. 4Joined during the year. 5On project appointment. 6Transferred from Social Sciences Division. 7Transferred from Entomology and Plant Pathology Division. 8Transferred from Genetic Resources Center. 9Transferred from Human Resources. 10Transferred from Physical Plant.

xxii

Abbreviations and acronyms

ADB = Asian Development Bank AGI = Agricultural Genetics Institute (Vietnam) ai = active ingredient AICRIP = All India Coordinated Rice Improvement Project ANR = apparent N recovery ANUE = agronomic N use efficiency AOB = ammonium–oxidizing bacteria ARA = acetylene-reducing activity ASL = Analytical Service Laboratories AWD = alternate wetting and drying BB = bacterial blight BIL = backcross inbred lines BPH = brown planthopper CEC = cation exchange capacity CGFG = Controlled Growth Facilities and Grounds CGIAR = Consultative Group on International Agricultural Research CIAP = Cambodia-IRRI-Australia Project CIMMYT = International Maize and Wheat Improvement Center CMS = cytoplasmic male sterile/sterility CNRRI = China National Rice Research Institute CREMNET = Crop and Resource Management Network CRIFC = Central Research Institute for Food Crops (Indonesia) CRRI = Central Rice Research Institute (India) CRU= controlled-release urea CRURRS = Central Rainfed Upland Rice Research Station (India) CV = coefficient of variation CWS = chopped wheat straw DAS = days after sowing DAT = days after transplanting DBS = days before sowing DH = double haploid DOA = Department of Agriculture (Thailand) DS = dry season DSR = direct-seeded rice

ES = Experiment Station ET = early tillage FAO = Food and Agriculture Organization FYM = farmyard manure GC = gas chromatography GXE = genotype by environment (interaction) GIS = geographic information system GLH = green leafhopper GM = green manure GMS = genealogy management system GR = glutathione reductase GRC = Genetic Resources Center HI = harvest index HPLC = high–performance liquid chromatography HYNet = Hybrid Rice Network IMGLP = interactive multiple–goal linear programming (model) INGER = International Network for Genetic Evaluation of Rice INGERIS = INGER Information System IP = intellectual property IPM = integrated pest management IPMNet = Integrated Pest Management Network IPMR = intellectual property management review IRBN = International Rice Blast Nursery IRGCIS = International Rice Genebank Collection Information System IRIS = International Rice Information System IRRC = Irrigated Rice Research Consortium IT = information technology LCC = leaf color chart LT = late tillage LUPAS = land use planning and analysis system MARDI = Malaysian Agricultural and Research Development Institute MAS = marker–aided selection MDA = malondialdehyde MHA = mobile humic acids

xxiii

NARES = national agricultural research and extension systems NARS = national agricultural research systems NBS-LRR = nucleotide-binding sites – leucine-rich repeats NCGR = National Center for Genomic Resources (New Mexico) NGO = nongovernment organization NIIL = near-isogenic introgression lines NNI = nitrogen nutrition index NPT = new plant type NRM = natural resource management PA = Public Awareness (Unit) PAGE = polyacrylamide gel electrophoresis PAR = photosynthetically active radiation PAU = Punjab Agricultural University (India) PCR = polymerase chain reaction PGSP = Philippine Grains Standardization Program PhilRice = Philippine Rice Research Institute PNUE = physiological N use efficiency PVP = plant variety protection QTL = quantitative trait locus RAPD = randomly amplified polymorphic DNA RAU = Rajendra Agricultural University (India) RFLP = restriction fragment length polymorphism RI = recombinant inbred RIFCB = Research Institute for Food Crops Biotechnology (Indonesia) RIL = recombinant inbred lines RSDA = rice supply and demand analysis (model) RTSV = rice tungro spherical virus

RUE = radiation use efficiency RYSTPAP = Rice Yield Estimation for Potential and Attainable Production (model) SCRIS = Santa Cruz River Irrigation Scheme SDC = Swiss Agency for Development and Cooperation SHU = Seed Health Unit SINGER = Systemwide Information Network for Genetic Resources SPAD = soil-plant analysis development SSB = striped stem borer SSR = simple-sequence repeat STS = sequence-tagged site TGMS = thermosensitive genic male sterile/sterility TMAH = tetramethylammonium hydroxide TPR = transplanted rice UCD = University of California-Davis UPLB = University of the Philippines Los Baños UPRIIS = Upper Pampanga River Integrated Irrigation System VECS = Visitors, Exhibition, and Conference Services WESVIARC = Western Visayas Integrated Agricultural Research Center WS = wet season Xoo = Xanthomonas oryzae pv. oryzae YSB = yellow stem borer

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Research programs Irrigated rice ecosystem

BREEDING TO BREAK YIELD CEILINGS: A SYSTEMS APPROACH 4 Hindsight and perspectives: yield improvements and C3 vs C4 rice 4 Breeding for resistance to rice tungro disease 5 Developing premium-quality rices with high yield potential 6 Further improvement of the new plant type 6 IR lines named as varieties 7 IR lines named as varieties for cool, highelevation areas 7 Comparison of stem borer resistance in new plant type lines and modern indica cultivars 7 Decline in yield potential of IR8 8 Quantitative trait loci (QTL) analysis 8 QTL analysis for seed germination 8 QTL reaction to heading date at tropical and temperate sites 8 Comparison of rice plant types with a view to adapt cultivation practices 9 Farmers' experience with hybrid rice in Bangladesh 10 CROP MANAGEMENT IN INTENSIVE RICE AND RICE-WHEAT SYSTEMS: RECONCILING HIGH PRODUCTIVITY AND ENVIRONMENTAL CONCERNS 11 Soil phosphorus as affected by fallowperiod management 11

Long-term effects of urea and green manure 14 Yield and soil nutrient changes in a long-term rice-wheat rotation 15 INCREASING WATER USE EFFICIENCY IN RICE CULTURE 17 Technologies and policies for agricultural water savings in China 17 Water management effects on rice-weed interactions in direct-seeded, irrigated systems 18 Nitrate and pesticide contamination of groundwater under rice-based cropping systems in the Philippines 20 IMPROVING PEST MANAGEMENT 22 Understanding variation in weed species responses to management in wet-seeded rice 22 Effect of Bt rice on the brown planthopper and its predator Cyrtorhinus lividipennis 22 IRRIGATED RICE RESEARCH CONSORTIUM 23 PROGRAM OUTLOOK 23

Irrigated rice ecosystem

The irrigated rice ecosystem produces 75% of the world’s rice, with nearly 40% of the world’s population dependent on the system for food. Asia’s population will increase by an estimated 1.6 billion people during the next 50 years and will require a 44% increase in production to maintain current per capita consumption. Rice production is the product of yield and area but increases in land area are no longer possible. Indeed, land area for rice production is declining because of degradation, urbanization, and industrialization. Rice yields must increase, and for the foreseeable future, the bulk of the increase will have to come from the irrigated ecosystem. Productivity must increase and that, in turn, will require more capital and knowledgeintensive management. The Irrigated Rice Ecosystem Research Program has three primary objectives: q breaking current yield barriers, q increasing the efficiency of crop production inputs, and q closing the yield gap while sustaining the irrigated lowland ecosystem. The Program has effective partnerships with national agricultural research and extension systems (NARES) through the Irrigated Rice Research Consortium to ensure that the work is implemented in local research programs and delivered to farmers.

Breeding to break yield ceilings: a systems approach
Hindsight and perspectives: yield improvements and C3 vs C4 rice J. Sheehy, J. Dionora, A. Ferrer, and P. Pablico It is often suggested that continuation of the existing trends in cereal yield would be sufficient to meet the future demand for food. But linear trends of the past 30 years can be extrapolated into the future only if there are no foreseeable limits to yield. However, the absorption of solar energy and its efficiency of use in the synthesis and retention of biomass sets the theoretical yield limit. The most concrete example of a yield limit comes from the records of the best entry in breeder’s irrigated trials of post-green revolution indica rice at IRRI. For the past 30 years, the average yield of the best entry was 8 t ha–1 during a 110-d growing season. That corresponded to a radiation use efficiency (RUE) of 1.8 g dry matter MJ–1 of intercepted photosynthetically active radiation (PAR), suggesting an absolute thermodynamic limit or yield barrier. Extrapolating the data for current average irrigated rice yields gives an average yield of 8 t ha–1 for 2019 and 10.8 t ha–1 for 2050. If it is assumed that the upper quartile of farmers obtain yields 25% greater than the average, then their corresponding yields for those years would equal 10 t ha–1 and 13.5 t ha–1. One might expect that farm yields would be about 80% of the best yields on research stations, such as IRRI, suggesting that best IRRI yields would be 12.5 t ha–1 in 2019 and 17 t ha–1 in 2050. Are such yields realizable and what could be done to achieve them? At first glance, one would not be

4

IRRI program report for 2000

optimistic because over the past 30 years at IRRI, the maximum yield of inbred cultivars of irrigated rice has not exceeded 10 t ha–1 (RUE of 2.2 g dry matter MJ–1 PAR). However, at IRRI, IR72 yielded 11.6 t ha–1 (RUE of 2.5 g dry matter MJ–1 PAR) in small plots with nets to prevent lodging, but 10.1 t ha–1 in plots where rice lodged. The new plant type (NPT), while not lodging, suffered substantial damage (>30% tillers) from the striped stem borer during grain filling, and average yield was 10 t ha–1. The maximum yield for the NPT was estimated as 12 t ha–1 (RUE of 2.6 g dry matter MJ –1 PAR). We concluded that the maximum achievable yield for irrigated C3 rice in experimental plots in the tropics was about 12 t ha–1, less than the value of 15 t ha–1 suggested by earlier work at IRRI. Thus we can be optimistic that rice cultivars with a yield potential of 12 t ha –1 will be bred. But progress will require improved lodging resistance and stem borer resistance. Nitrogen management will then be the key to success, with the introduction of a more efficient and intensive N management system essential to enable new rice cultivars to realize their potential. New, higher yielding C3 rice crops would enable the current linear yield trend for irrigated rice to continue for another 20 years. Nonetheless, yields of about 12 t ha–1 represent the yield potential for rice in the tropics with its current photosynthetic pathway (C3). RUE will have to rise to the average for maize (3.3 g dry matter MJ–1 PAR) to enable the linear trend in irrigated rice to continue beyond the year 2020, which means introducing a maize-like photosynthetic pathway (C4) to rice. As well as increasing yields, a C4 rice plant could, given an increasing atmospheric concentration of carbon dioxide, greatly improve water use efficiency, thus contributing to water savings in irrigated systems. Breeding for resistance to rice tungro disease G.S. Khush and P.S. Virk The breeding strategy for the management of tungro disease was, until recently, based on using vector (green leafhopper [GLH]) resistance. However, resistance to GLH breaks down after 4–5 years, owing to change in the vector’s virulence or adapta-

tion, or both. Several sources of resistance to tungro virus (RTSV) were recently identified at IRRI. These are Utri Merah, Utri Rajapan, ARC11554, Habiganj DW8, and three accessions of Oryza rufipogon. The donors for resistance, however, had poor plant type and genes for RTSV resistance had to be transferred into an improved plant type. Many advanced lines were bred and evaluated in replicated field trials in areas with reported high RTSV incidence in the Philippines, Indonesia, and India during 1995-98. Several advanced breeding lines and a dozen lines representing different sources of resistance to the RTSV were identified. The performance of the elite RTSV-resistant lines is given in Table 1. IR69726-29-1-2-2-2 was tested by the Rice Varietal Improvement Group of the Philippine Seed Board for three seasons and elevated to multilocational trials. It was then recommended as a stop-gap variety for tungro-endemic areas. A sister line, IR69726-116-1-3, was released as a variety in Indonesia. IR64 has excellent eating quality and stable yield, making it a popular variety among farmers in several countries. It was resistant to GLH at the time of release but its vector resistance has broken down. We crossed IR64 with three accessions of O. rufipogon found resistant to RSTV and three backcrosses were made to obtain IR64-type lines with resistance. Several backcross lines were evaluated in the replicated yield trials and a tungro nursery. Many lines are phenotypically similar to IR64, possess its grain quality, and show excellent RTSV resistance. These lines were in the Philippine National Cooperative testing program and IR73885-1-

Table 1. Elite breeding lines with tungro resistance. IRRI, 2000 dry season. Grain Days to yield maturity (t ha–1) 5.6 5.6 4.4 5.5 5.8 5.6 5.9 5.8 5.6 5.7 5.6 126 125 134 121 119 120 123 123 125 124 123 Source of resistance

Breeding line

IR69726-29-1-2-2-2 IR69726-41-2-3 IR69726-116-1-3 IR69727-37-2-1-3-2 IR71606-1-1-4-2-3-1-2 IR71606-2-1-1-1-3-3-1-2 IR73885-1-4-3-2-1-4 IR73885-1-4-3-2-1-6 IR73885-1-4-3-2-1-10 IR73887-1-8-2-1 IR73888-1-2-7

Utri Merah Utri Merah Utri Merah Utri Rajapan Habiganj DW8 Habiganj DW8 O. rufipogon O. rufipogon O. rufipogon O. rufipogon O. rufipogon

Irrigated rice ecosystem

5

4-3-2-1-6 was recommended as a stop-gap variety for tungro endemic areas. Resistant lines evaluated by several farmers in an Iloilo-IRRI project performed well in the 2000 wet season (WS). Developing premium-quality rices with high yield potential Crosses were made during the early 1970s between Basmati 370 and improved indica lines possessing intermediate amylose content and intermediate gelatinization temperature. Large segregating populations were grown and a few lines with short stature were selected. Segregants with less sterility and good plant type were selected from intercrosses of those lines and evaluated for amylose content, gelatinization temperature, aroma, and grain elongation. Intermating of selected lines, followed by selfing, was done for several cycles over the years to combine all the grain quality characteristics. Other Basmati-type varieties released in India and Pakistan, such as Pusa Basmati 1 and Basmati 385, were also used in crosses. After several cycles of hybridization and selection, improved-plant-type lines with short stature that match the grain quality characteristics of Basmati rices have been selected. This year, one of the lines, IR65610-24-2-4-2-6-3,

was released as MTL 233 in Vietnam. A number of lines are being evaluated in replicated yield trials at IRRI and in observational nurseries in India and Pakistan (Table 2). Aroma, until recently, was evaluated by laboratory procedure that categorized cooked samples by sniffing. We now collaborate with USDA-ARS (Rice Research Unit, Beaumont, Texas, USA) to estimate the quantity of 2-acetyl-1-pyrroline, a key compound known to be responsible for aroma in Basmati rices. Further improvement of the new plant type Several NPT lines developed after 1995 from tropical japonica germplasm have large panicles, low tillering capacity with sturdy stems, and match the NPT ideotype. Some of those lines outyielded IR72 by 15–20% in replicated yield trials. One of the lines, IR64446-7-10-5, was released as Dianchao 3 in Yunnan Province, China, where it yielded more than 13 t ha–1. A selection from IR69097-AC2-1 was designated as DS2 and is being evaluated in replicated yield trials in Yunnan as a possible highyielding variety. The NPT lines have short bold grains with low amylose content typical of japonica rices. They lack resistance to RTSV and brown planthopper (BPH), making them suitable for temperate areas where rice

Table 2. Characteristics of elite Basmati-type breeding lines developed at IRRI. Plant height (cm) 91 83 102 109 116 102 97 104 103 105 86 98 105 95 106 107 91 Growth duration (d) 112 116 119 116 113 110 112 112 125 114 119 126 123 122 120 127 126 Grain length (mm) 7.32 7.04 6.92 6.94 7.84 7.04 6.96 7.90 6.74 7.86 6.50 6.72 7.08 7.22 6.66 6.78 7.28 Amylose content (%) 21 23 23 18 22 22 24 22 19 23 24 22 22 25 21 22 20 Gelatinization temperaturea Grain Pyrroline elongation (ppb)

Breeding line IR65610-24-2-4-2-6-3b IR65610-38-2-4-2-6-3 IR69745-251-2-2-1-1 IR70422-95-1-1 IR70445-146-3-3 IR71137-184-3-2-3-3 IR71137-243-2-2-3-3 IR71139-50-2-1-1-2 IR71144-176-3-2-3-2 IR71730-51-2 IR72860-68-1-1-1 IR72860-80-3-3-3 IR72860-109-2-3-2 IR72861-77-2-3-2 IR72870-120-1-2-2 IR72883-10-2-2-2 IR72883-169-2-2-2
a

Aroma

HI>L I>L L HI HI>I HI>I L I>L L L L L HI>I L I HI>I>L HI

Strong Strong Strong Strong Strong Strong Strong Strong Strong Strong Strong Strong Strong Strong Strong Strong Strong

1.84 1.92 1.94 1.85 1.99 1.81 1.92 1.82 1.97 1.84 2.08 2.02 1.86 1.77 1.96 1.68 1.73

71 405 126 267 274 432 398 556 540 401 524 663 224 416 324 258 236

Based on alkali digestibility: L = low, I = intermediate, HI = high intermediate, H = high. bReleased in Vietnam as MTL 233.

6

IRRI program report for 2000

with japonica grain quality is preferred and RTSV and BPH are not a serious problem. Preference in the tropics and subtropics is for long, slender grains with intermediate amylose content, and wide-adaptation resistance to RTSV and BPH is essential. A high number of crosses between NPT lines and elite indica varieties and breeding lines were made to improve the NPT lines for grain quality and disease and insect resistance. Advanced breeding lines with long slender grains and resistance to bacterial blight, blast, RTSV, BPH, and GLH were selected from those crosses. Those lines are in replicated yield trials. IR lines named as varieties Ten breeding lines from the irrigated breeding program were named as varieties in six countries during 2000 (Table 3). This brought the number of IRRI breeding lines named as varieties by national programs to 327. IRRI lines named as varieties for cool, highelevation areas G.B. Gregorio, A.N.R. Monroy, R.D. Mendoza, J.P. Roxas, D. Senadhira, G.S. Khush, T.F. Padolina1, E. Corpuz, H.C. dela Cruz1, and M.D. Cadatal2 Three breeding lines (IR9202-25-1-3, IR61336-4B14-3-2, and IR61608-3B-20-2-2-1-1) from the coldtolerant rice-breeding program were named as varieties for high-elevation areas in the Philippines (Table 4). Aside from having improved tolerance for cold temperature during WS, the varieties possess
Table 3. Breeding lines from the IRRI irrigated rice breeding program named as varieties during 2000. Breeding line IR64446-7-10-5 IR59682-132-1-1-2 IR68305-18-1 IR69726-116-1-3 IR60819-34-2-1 IR59552-21-3-2-2 IR31892-100-3-3-3-3 IR65610-24-3-6-3-2-3 IR64724-195-1-2-2-1 IR48563-22-3-2-3 IR62871-264-3-4 IR62871-175-1-10 IR9202-25-1-3 Name given Dianchao 3 Tukad Balian Tukad Unda Tukad Petanu Bondoyudo Kalimas Celebes I MTL 233 MTL 241 IR48563 Sahel Fajr PSBRc 92 Country where named Yunnan, China Indonesia Indonesia Indonesia Indonesia Indonesia Indonesia Vietnam Vietnam Papua New Guinea Iran Iran Philippines

good eating qualities, nonshattering, high milling recovery (86%), and resistance to insect pests and diseases. This brought the number of IRRI breeding lines named as varieties in cool, high-elevation areas in the Philippines to five. Two others were released in 1995. The Rice Varietal Improvement Group of the Philippines identified the cold-tolerant lines IR60058-4B-4-1-1, IR61728-4B-2-1, and IR624437-2-2-2-1 for prerelease, multiplication, and distribution to farmers for dry-season (DS) planting in cool areas. Comparison of stem borer resistance in new plant type lines and modern indica cultivars Zeng-Rong Zhu, A.M. Romena, and M.B. Cohen Field experiments in 1999 compared stem borer damage, resistance, and egg mass density in two NPT lines (IR65564-22-2-3 and IR68011-15-1-1) and two modern indica varieties (IR64 and IR72). Damage in DS was significantly higher for the two NPT lines than for the two indica varieties at 90 and 98 days after transplanting (DAT). In WS, damage for both NPT lines was significantly higher than on IR64, but not for IR72, at 90 and 98 DAT. The NPT lines had significantly higher densities of yellow stem borer (YSB) egg masses at 90 and 98 DAT in the DS. In WS, YSB egg masses peaked at 75 DAT and were generally highest on IR65564, significantly so at 75 and 90 DAT. IR68011 often had the highest densities of striped stem borer (SSB) egg masses, significantly so at 75 DAT in the DS and at 75 and 90 DAT in the WS. When artificially infested in field cages, the four rice lines did not differ significantly in the proportion of either YSB or SSB that completed development from egg to adult in either season. Similarly, there was no consistent effect of rice line on male or female weight or developmental time. Our results suggest that the NPT lines had higher levels of damage in the field experiments than in cages primarily because they were more attractive to ovipositing stem borers, not because they were more susceptible to larval feeding. Behavioral experiments in a wind tunnel will further test the attractiveness of NPT lines to stem borer adults.

Irrigated rice ecosystem

7

Table 4. IRRI breeding lines from the cold-tolerant rice breeding program named as varieties in the Philippines during 2000. Breeding line IR9202-25-1-3 IR61336-4B-3-2 IR61608-3B-20-2-2-1-1 Parentage IR2053-521-1-/K116//KN-1B-361-1-8-6-9-1 IR44535-22-3-3-/IR8866-30-3-1-4-2 IR32429-47-3-2-//Dobongbyeo/Moroberekan Philippine Seed Board name PSBRc 92 PSBRc 94 PSBRc 96 Local name Sagada Hungduan Ibulao

Decline in yield potential of IR8 S. Peng Experiments at IRRI in 1996 and 1998 DS showed that IR8 yielded 1–2.5 t ha–1 less than its yield potential of 9.5–10 t ha–1 reported 30 years ago. Hypotheses given to explain the decline in yield potential of IR8 include q intensive rice cultivation caused changes in the soil-flooded water system, q climate change over the years, and q genetic modifications occurred within the IR8 seed. IR8 seed harvested in 1968 DS was obtained from the IRRI Genetic Resources Center (GRC) and compared with IR8 seed continuously grown for 30 years at IRRI. The IR8 from GRC (called old IR8) was multiplied in 1998 WS. The continuously grown IR8 was called new IR8. The old and new IR8 were grown in 1999 WS and 2000 DS. The results suggest that genetic changes have not occurred within the IR8 seed continuously grown for 30 years. The next step is to investigate what changes might have occurred in the soil-floodwater system, and their possible contribution to the yield decline. Quantitative trait loci (QTL) analysis Y. Fukuta Chromosomal regions related to high yielding and ripening ability were detected using QTL analysis. Particular attention was paid to morphological and physiological characters. During 2000 DS and WS, Milyang23/Akihikari recombinant inbred lines (RIL) and Nipponbare/Kasalath//Nipponbare backcross inbred lines (BIL), were used for QTL analyses of heading date, culm length, panicle length, tiller number, panicle number, N concentration, spikelets per plant, harvest index, leaf shape, leaf size, seed germination, and tolerance for iron toxicity.

QTL ANALYSIS FOR SEED GERMINATION

Seed germination is one of the complex characters related to dormancy, germination, and senescence in rice (O. sativa). QTL analysis using RILs derived from the cross between an indica variety, Milyang 23, and a japonica variety, Akihikari, detected a total of 11 QTLs in six chromosomes—1 (3), 2 (1), 4 (1), 5 (2), 9 (1), and 11 (3). The 11 QTLs were classified into five groups—those related only to dormancy (1), to germination (5), to senescence (1), to both dormancy and germination (3), and to dormancy, germination, and senescence (1). Analysis of gene expression over time after soaking found that functional genotypes changed during early and late germination stage in some QTLs. Among them, three QTLs changed functional genotype from Akihikari to Milyang 23 and two QTLs changed functional genotypes from Milyang 23 to Akihikari. The results indicate that the dynamics of gene expression can be found in seed germination by use of QTL analysis.
QTL REACTION TO HEADING DATE AT TROPICAL AND TEMPERATE SITES

A total of 26 QTLs for heading date were detected from 28 repetitions at 10 sites in tropical and temperate regions using 191 RILs from a cross between Milyang 23 and Akihikari. The study was at IRRI in 2000 DS and at Japanese sites in Kyushu region in 1995 and Tohoku region in 1999. Because the QTL corresponding to the photoperiod-sensitive gene Se1 on chromosome 6 was not detected in these analyses, it was estimated that the two parents have the same allele on the locus. In the temperate regions, it was found that two QTLs with strong functions on chromosomes 7 and 11 acted mainly with the relationship of mutual help. Although the two QTLs were not detected in the tropical region, four specific QTLs were recog-

8

IRRI program report for 2000

nized on chromosomes 2, 3, 9, and 10. It was hypothesized that the genes relating to vegetative growth played an important role in segregation in the tropical region and the photoperiod-sensitive and vegetative growth genes acted together in temperate regions. It was assumed that the QTL on chromosome 7 corresponded to a photoperiod-sensitive gene, E1. Comparison of rice plant types with a view to adapt cultivation practices P. Siband Different rice plant types were studied with respect to morphological and behavioral characteristics, with a view to adapting cultivation practices to new varieties and current on-farm management trends. IR72 and two hybrid varieties (IR68284H and IR73854H) were used in 1999. The NPTs IR6556444-2-3, IR69853-70-3-1-1, and IR68552-100-1-2-2 were used in 2000. These were numbered V1-V6 (Fig. 1) and compared during 1999 WS and 2000 DS in split-plots where main treatments were varieties, and secondary treatments were 1) plant population density, 2) level of N application at midtillering or at panicle initiation, 3) plant thinning at different growth stages, or 4) change of sourcesink balance by removing two leaves or half of the panicle. Compared with IR72, the NPTs showed a strongly lower tillering capacity and lower number

Spa 240 220 200 180 160 140 120 100 100 200 300 400 PaM2 500 600
V1 V2 V3 V4 V5 V6

2. Variation in number of spikelets panicle-1 (Spa) with panicle population density (PaM2). IRRI, 2000.

PaP 40 35 30 25 20 15 10 5 0 0 20 40 PLM2 1. Variation in number of panicles plant –1 (PaP) with plant population density (PLM2). IRRI, 2000. 60 80 100
V1 V2 V3 V4 V5 V6 HYB HYB NPT NPT NPT IR72 IR68284H IR73854H IR65564-44-2-3 IR69853-70-3-1-1 IR68552-100-1-2-2

of panicles per plant at all population densities (Fig. 1). However, this did not reduce their regulating capacity of panicles per square meter (Fig. 2). Hybrids also had a slightly lower tillering rate than IR72. The size of panicles increased as panicle density decreased, but the relationship widely varied with variety (Fig. 2). For a given panicle density, spikelets per panicle were higher for hybrids and NPTs, particularly for V5, than for IR72 (V1). The close regulation of panicle per plant and spikelets per plant strongly reduced the variation of later yield components. However, V5 and V6 single-grain weights decreased with increasing number of grains per square meter. This could be related to poor grain filling. Hybrid plants were taller than IR72, whereas that character was quite variable among NPTs. Unit stem weights were slightly higher for hybrids, and much higher for NPTs, than for IR72. Stems, leaves, and roots appeared thicker for NPTs, which had a high dry-matter cost to grow a unit of leaf area or root length. On the other hand, leaves were thinner for hybrids (Fig. 3). Hybrids and IR72 had the same dry matter growth rate (variations of tillering capacity and leaf thickness getting compensating effects), whereas NPTs were significantly lower (Fig. 4). Soil plant analysis development (SPAD) values observed at a given N status (nitrogen nutrition index—[NNI]) were higher for NPT and lower for hybrid varieties than for IR72 (Fig. 5). This could result in variation in varietal SPAD calibration. Vari-

Irrigated rice ecosystem

9

SLA cm2 g-1 320 300 280 260 240 220 200
V1 V2 V3 V4 V5 V6

SPAD 48 46 44 42 40 38 36
V1 V2 V3

180

34
160 30 40 60 80 70 DAS 80 90 100

32 0.9 1.0 0.7 0.8 NNI 5. Relationship between nitrogen nutrition index (NNI) and SPAD value of IR72 (V1), hybrid (V3) and NPT (V5) varieties. V1 SPAD = 14.0 (+/- 4.4) NNI + 28.0 (+/-1.6), n = 16, R2 = 0.41. V3 SPAD = 8.4 (+/- 1.7) NNI + 29 (+/-1), n = 16, R2 = 0.64. V5 SPAD = 23.0 (+/- 2.1) NNI + 27.0 (+/-0.8), n = 16, R2 = 0.90. IRRI, 2000. 0.4 0.5 0.6
NNI 1 0.9 0.8

3. Comparison of specific leaf area (SLA) among varietal types. IRRI, 2000.

30 0.3

Dry matter (g m-2) 1400 1200 1000 800 600 400 200 0 25
NPT varieties DM = 20 (±0.7) DAS –949 (±68) n = 33 R2 = 0.95 IR72 and hybrid varieties DM = 27 (±0.8) DAS –11.86 (±56) n = 33 R2 = 0.98 V1 V2 V3 V4 V5 V6

0.7 0.6 0.5
V1 V2 V3 V4 V5 V6

35

45

55

65 DAS

75

85

95

4. Growth rate of NPTs compared with other varietal types. IRRI, 2000.

ety V5, whose roots were particularly thick, and thus had root length limited, seemed to increase its NNI at a slower rate than other varieties after N application (Fig. 6). Removing the two upper leaves 15 d after panicle initiation changed the unit grain weight distribution, which differed among varieties (Fig. 7). For IR72 and the hybrid varieties, decreasing the source increased the frequency of unfilled grains. For NPT varieties, it increased the frequency of partially filled grains, showing a lower capacity to adjust their number of grains to be filled, with possible consequences for grain quality.

0.4 –1 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 DAPI

6. Evolution of nitrogen nutrition index (NNI) after N application at panicle initiation. IRRI, 2000.

Farmers’ experience with hybrid rice in Bangladesh M. Hossain, M. Husain3, and A. Janaiah Because the research system in Bangladesh had not developed appropriate hybrids, the government encouraged the private sector to import hybrid rice

10

IRRI program report for 2000

Frequency 30
25 20 15 10 5 0 0

V3 (hybrid) Control Source restricted

V5 (NPT)

10

20

30

40 0

10

20

30

40

Grain weight 7. Histograms of individual grain weight from populations of hybrid (V3) and NPT (V5) varieties under restricted source (two leaves removed) and control (no leaf removed). IRRI, 2000.

seed in 1998 to partially cover a shortage of rice seed after devastating floods. Four seed companies and one nongovernment organization (NGO) received permits to import hybrid rice seed for 1999 DS (boro). About 600 t of seed of four hybrid varieties from India and one variety from China were imported. Estimates from seed sales data are that about 23,700 ha (out of 3.5 million ha under boro rice) were planted to hybrid rice in 1999. We did an evaluation in collaboration with the Research and Evaluation Division of the Bangladesh Rural Advancement Committee (BRAC), the NGO involved in marketing the hybrid seed. The principal objective was to get farmer feedback on the performance of hybrid rice vis-à-vis the inbred varieties. The evaluation indicated that the hybrid rice technology was introduced prematurely in Bangladesh and hybrid rice earned a bad name because a majority of the farmers grew Alok-6201, an Indian variety that performed poorly. Also, the cost of seed was high because it was imported. Major implications arising from the evaluation were q High-quality, local hybrid rice varieties, suitable for Bangladesh, should be developed. q Domestic seed production should be expedited. q Hybrids suitable for a rainfed environment and resistant to biotic stresses should be explored.

Crop management in intensive rice and rice-wheat systems: reconciling high productivity and environmental concerns
Soil phosphorus as affected by fallow-period management S.B. Bucher4, W.L. Larazo, and A. Dobermann5 Little is known about the effects of dry fallow periods, time of tillage, and time of straw incorporation on soil P dynamics in double-crop rice systems. A project financed by the Swiss Agency for Development and Cooperation (SDC) hypothesized that either early rice straw incorporation or early tillage after rice harvest would increase P availability to the subsequent rice. A field experiment on a Typic Tropaqualf (59% clay, 20 g kg–1 total C, 6.7 pH, 10 mg kg–1 Olsen P, and 454 mg kg–1 total P) at IRRI ran from 1997 to 2000. Eight treatments were arranged with early tillage (ET) at start of fallow period and late tillage (LT) at end of fallow period as main plots. Straw management (+S = straw incorporated and –S = no straw incorporated) and fertilizer (NPK = NPK fertilizer, NK = no P fertilizer) were strip plots inside the main plots. Fertilizer rates (kg ha–1) were 180 N, 20 P, and 30 K in DS and 100 N, 20 P, and 30 K in WS. A few days after harvest of the previous crop, rice stubble was removed in all –S plots. In ET+S plots, rice was cut at ground level before straw incorporation. At 1–2 wk after harvest, a 10-cm depth rototillage was done in all ET plots, and LT plots

Irrigated rice ecosystem

11

were left undisturbed. In LT+S plots, rice stubble was left standing in the field during the entire fallow. At 2–3 wk before transplanting the next rice crop, all plots were flooded and LT plots were plowed 10–15 cm deep, including incorporation of standing stubble in +S treatments. Measurements of soil P dynamics began in the 1998 DS (3rd crop) and continued until the end of the 2000 DS (7th crop). The P fertilizer rate was 20 kg ha–1. Plantavailable soil P in 0–10 cm soil depth was determined on fresh soil as anion exchange resin extractable P (AER-P). A greenhouse experiment with four treatments in undisturbed soil blocks was conducted for two seasons. The main plot was soil water regime during the fallow period (drying = soil drying during fallow, wet = soil kept water-saturated during fallow). The subplot in the first season was tillage (ET and LT as in the field experiment). It was replaced in the second season by straw (+S = early tillage with straw incorporation at 5 t dry matter ha–1 at start of fallow, –S = early tillage with no straw incorporated). Irrigated rice was grown in both seasons and managed similarly to the field experiment. Extractable iron (Fe) was measured at 0–10 cm soil depth, and redox potential (Eh) was measured at 5 and 15 cm soil depth. In the field experiment, ET and straw incorporation increased P availability (Fig. 8). Averaged across all sampling dates and all straw and fertilizer treatments, ET increased AER-P by 0.6-2.5 mg kg–1 dry soil, which was significant for NPK plots but not NK plots. This indicates that tillage affected freshly added P more than native soil P.

The increase in AER-P during rice crops following ET as compared with LT was negatively correlated with the amount of rainfall during the fallow period (r = –0.92, P = 0.03). This could be attributed to enhanced topsoil drying with ET. Between January 1998 and March 2000, the average AER-P concentration decreased at a rate of 2.5 mg kg–1 dry soil yr–1. In the NPK treatment, average AER-P decreased from 13 mg kg–1 in 1998 to 8 mg kg–1 in 2000, even though the estimated P input-output balance during this period was positive. The initial two fallows were sufficiently dry for substantial soil drying, but the subsequent three fallows (1999-2000) were extremely wet and soil water never dropped below 45 g H2O 100 g–1 fresh soil. Because of the wet soil, more P likely remained bound to amorphous Fe compounds and was not extractable with the resin. The greenhouse experiment confirmed that soil drying during the fallow, as compared with the soil remaining water-saturated, increased P availability to rice (Table 5). The ratio of acid ammonium oxalate extractable iron (FeOx) to citrate dithionite extractable iron (FeCD) suggests that soil drying promoted re-crystallization of amorphous FeIII-FeII hydroxides with a high P sorption capacity, which accumulated under flooding. The ratio of extractable FeII:(FeII+FeIII), an index for the oxidation status of iron oxides, indicates that thorough soil drying rendered FeIII oxides more resistant to reductive dissolution after reflooding. The Eh at 5 and 15 cm depth throughout the cropping season was 100–200 mV higher after a dry fallow than after a water-saturated fallow. Soil drying dur-

Table 5. Effects of soil drying during the fallow (as compared with leaving the soil water-saturated), early tillage at the start of the fallow (as compared with late tillage at the end of the fallow), and rice straw addition at the start of the fallow (as compared with no straw addition) on anion exchange resin extractable P (AER-P), oxalate extractable Fe (FeOx), citrate-dithionite extractable Fe (FeCD), citrate extractable Fe (FeC), EDTA-BPDS ethylene diaminetetraacetic acid-bathophenanthroline disulfonate) extractable FeII and FeIII, and Eh at 5 and 15 cm soil depth. Results are averaged for all sampling dates during the entire flooded period in a two-season greenhouse experiment. IRRI, 2000. Treatment Season I Soil drying Early tillage Season II Soil drying Straw AER-P (mg kg–1) FeOx (g kg–1) FeCD (g kg–1) FeOx : FeCD –0.18** ns FeC (g kg–1) FeII : (FeII + FeIII) Eh, 5 cm (mV) Eh, 15 cm (mV)

+2.6** ns

–2.8** ns

ns ns

–2.0*** ns

–0.25*** ns

+ 90** ns +100ns –100***

+220** ns

+2.1** ns

–3.0*** +0.4*

ns ns

–0.19** ns

– –

–0.41*** +0.07**

+170* –90***

12

IRRI program report for 2000

Fallow 300 Mean temperature
Rainfall (mm)

1998 dry season

Fallow

1998 wet season

Fallow

1999 wet season

Fallow

1999 wet season

Fallow

2000 dry season

Climate data

200 100 0 25 Rainfall

AER extr. P(mg kg–1 dry soil)

Anion exchange resin extr. P in NPK plots 20 15 10 5 0 15 Anion exchange resin extr. P in NK plots 10 5 0
Harvest 4 DAT 21 DAT 42 DAT 63 DAT

Early tillage, no straw Early tillage, with straw Late tillage, no straw Late tillage, with straw

AER extr. P(mg kg–1 dry soil)

Harvest

Harvest

Harvest

63 DBT

63 DBT

63 DBT

42 DBT

42 DBT

42 DBT

21 DBT

21 DBT

21 DBT

End of fallow 2 DBT

End of fallow

End of fallow 2 DBT

8. Anion exchange resin extractable P dynamics from 1997 to 2000 as affected by tillage and rice straw incorporation in NPK- and NK-fertilized plots, in relation to rainfall and temperature. Flooded phases (cropping seasons) are shaded dark gray; nonflooded phases (fallow periods) are shaded light gray. IRRI, 2000.

End of fallow 2 DBT

Mid-fallow

Mid-fallow

Mid-fallow

Mid-fallow

21 DBT

42 DBT

63 DBT

2 DBT

Irrigated rice ecosystem

13

ing the fallow significantly increased plant P uptake by 39% in the first season. In summary, a dry fallow increased P availability to a subsequent flooded rice crop. Early tillage at the start of the fallow additionally increased P availability by promoting soil drying. Early straw incorporation had a beneficial effect on AER-P in the field but not in the greenhouse. Soil conditions during fallow affect the dynamics of redox potential, iron compounds, and P during a succeeding rice crop. Periodical soil drying may reverse trends of declining P availability by promoting recrystallization of amorphous iron oxides that accumulated during the flooded phase. Soil aeration during fallows can be manipulated through ET at the start of the fallow, which helps maintain soil P availability to rice, particularly if combined with an early straw incorporation to increase the soil P balance. We need to verify these findings in diverse field conditions. Long-term effects of urea and green manure J.K. Ladha, D. Dawe, T.S. Ventura, U. Singh, W. Ventura, and I. Watanabe Periodic monitoring of changes in N uptake and soil N pools is rarely done in long-term experiments. Such measurements, however, can provide valuable insight into possible causes of observed yield trends and the implications of these trends for yield sustainability. In addition, most tropical experiments were designed to study yield trends with use of commercial N fertilizer, while ignoring green manure (GM) as an alternative source of N. We report results of a 14-year experiment at IRRI designed to compare long-term effects of in situ grown GM (azolla and sesbania) and urea fertilizer. The experiment was conducted in a silty clay with two crops of rice grown each year. The treatments were no applied N, urea, Sesbania rostrata, and Azolla microphylla. Urea was split-applied at 50–80 kg N ha–1. Azolla was grown for 42–62 d and incorporated into the soil three to four times during each rice crop. Sesbania was grown in situ for 46– 67 d before incorporation. Nitrogen inputs from the three sources ranged from 69 to 75 kg ha–1 in DS and 68 to 88 kg ha–1 in WS. In the no-N control, yields after 25 crops averaged 4 t ha–1 crop–1 in WS and 4.4 t ha–1 crop–1 in

DS. Green manure and urea application increased grain yield by more than 1 t ha–1 crop–1 in the WS and 2 t ha–1 crop–1 in the DS. There were no significant differences in grain yields and rice N uptake with azolla, sesbania, and urea during the WS. Grain yield during the DS was significantly higher with azolla than with sesbania and urea. Using data from 27 crops, a linear regression analysis was performed to estimate the yield trends. The LIMDEP statistical package was utilized to determine the magnitude of yield trends after controlling the effects of changing weather and N input during the course of the experiment. The coefficients of the time variable were negative (Table 6). The magnitude of the yield decline in the WS ranged from 94 kg ha–1 y–1 in the no-N plots to 157 kg ha–1 y–1 in the sesbania treatment. Significant yield decline in the DS ranged from 139 kg ha–1 y–1 in the azolla treatment to 212 kg ha–1 y–1 in the urea treatment. Similar rates of yield decline in the azolla, sesbania, and urea treatments in both seasons indicated that the application of GM did not help arrest the yield decline. Additional sets of regressions were estimated to provide further insights underlying the estimated yield trends. In the WS, the coefficient on the time variable in a regression of N uptake on N input, solar radiation, and time was negative but not statistically significant in any of the four treatments. However, in a regression of yield on N uptake, solar radiation, and time, the coefficient on the time variable was negative and statistically significant (P < 0.05) in all treatments, indicating a decline over time in the ability of the plant to convert N uptake to grain yield. This accounted for 82% of the yield decline, across the four treatments. The same pattern was observed in the DS but the coefficients on the time variables in the regressions were not statistically significant. The decline in grain yield without a decline in crop N uptake may indicate that N was not available to the crop at critical growth phases. We speculate that there was a change through time in the pattern of soil N mineralization and availability to the crop. This is likely to happen when a soil remains continuously submerged and frequently puddled with incorporation of crop residue (root and stubble) of high C-N ratio. After 27 crops, the cumulative N balances were positive for the four treatments (Table 7). There was

14

IRRI program report for 2000

Table 6. Regression analysis of rice yield for N input, solar radiation, and time trend for the wet and dry season for 14 years at IRRI. IRRI, 2000. Independent variables Treatment Constant (kg ha-1) Wet season No applied N Urea Sesbania Azolla Dry season No applied N Urea Sesbania Azolla N input (kg ha-1) naa 25.8* 4.1ns 9.8ns Radiation (KJ m-2d-1) Trend (kg ha-1 yr-1) R2

4808** 3727ns 4703ns 5064*

–0.01ns 0.05ns 0.06ns 0.02ns

–94* –152** –157* –141* –63ns –212** –205** –139*

0.39 0.49 0.39 0.50

3442* 743ns 563ns 0.47ns

na 61** 40** 42**

0.06ns 0.14ns 0.20** 0.21**

0.08 0.82 0.81 0.85

Table 7. Nitrogen balance sheet for lowland rice soil to 50-cm depth after 27 rice crops. IRRI, 2000. Fertilizer treatment Crop removal (kg ha-1) (A) 1656c 2598b 2707ab 2781a Change in soil N (kg ha–1) (B) – 8bc –134c 344ab 541a Fertilizer input (kg ha–1) (C) 0 1710 2001 1782 Other inputsa (kg ha–1) (D) 405 405 405 501 N balance (A+B)–(C+D) Total 1244a** 348b* 646b** 1039a** Per cropb 46 13 24 38

No applied N Urea Sesbania Azolla
a

Other inputs include N from rain and irrigation water, P fertilizer, and pesticides. bN gains per crop.

no significant change in total soil N content in the no-applied N and urea treatments, whereas it increased after 27 crops by 344 kg ha–1 in the sesbania treatment and 541 kg ha–1 in the azolla treatment. Conservation of the soil N status and positive N balances (13 to 46 kg ha–1 crop–1), in spite of the high amounts of N removed, reflect N contributions from nonsymbiotic nitrogen (N2) fixation (Table 7). In addition, sesbania and azolla added an estimated 57–64 kg N ha –1 crop –1 through symbiotic N 2 fixation. The results demonstrate that biological N2 fixation plays a vital role in replenishing the soil N in rice-rice cropping systems. Yield and soil nutrient changes in a long-term rice-wheat rotation J.K. Ladha, A.L. Bhandari6, H. Pathak, A.T. Padre, D. Dawe, and R.K. Gupta7 Major improvements in the productivity of rice and wheat have occurred in the Indo-Gangetic Plains of South Asia since 1965-66. However, yields on ex-

perimental farms have stagnated or declined since the 1980s. We analyzed the results of a 14-year rice-wheat experiment at Punjab, India. Soil had been archived and plant nutrient removal measured, which provided an opportunity to examine the long-term effects of fertilizer on soil nutrient pools and examine the reasons for the observed yield trends in the various nutrient management systems. The experiment included two crops per year (rice Jul-Oct and wheat Nov-Apr) with 11 treatments. The treatments comprised application of different combinations of inorganic and organic sources of nutrients to rice and wheat at the recommended levels of N (120 kg ha–1), P (26 kg ha–1), and K (25 kg ha–1). Inorganic NPK were applied at 50, 75, and 100% of the recommended levels to rice and wheat. Other treatments included organic nutrients from farmyard manure (FYM), chopped wheat straw (CWS), and GM (S. aculeata). Sesbania was grown for 7–8 wk before the rice crop, and an appropriate amount of sesbania was incorporated into the soil a

Irrigated rice ecosystem

15

Table 8. Average rice and wheat yields and yield trends for 14 years of cropping (1984-97) in Ludhiana, India. N treatmenta Rice Wheat Av yield (t ha–1) Rice Yield change (t ha–1 y–1) –0.05 –0.10 –0.08 –0.09 –0.11 –0.08 –0.10 –0.07 –0.13 –0.11 –0.12 P value Av yield (t ha–1) Wheat Yield change (t ha–1 y–1) 0.02 –0.02 –0.03 –0.04 –0.04 –0.02 –0.01 –0.03 –0.03 –0.04 –0.03 P value

No fertilizer 50% NPK 50% NPK 75% NPK 100% NPK 50% NPK + FYMb 75% NPK + FYMc 75% N, 50% PK + CWSb 87.5% N, 75% PK + CWSc 50% NPK, 50% N in GM 75% NPK, 25% N in GM
a

No fertilizer 50% NPK 100% NPK 75% NPK 100% NPK 100% NPK 75% NPK 100% NPK 100% NPK 100% NPK 75% NPK

2.05 4.12 4.70 5.26 6.20 5.64 5.90 5.10 5.72 6.20 6.44

0.057 0.025 0.007 0.004 0.002 0.022 0.009 0.049 0.001 0.007 0.008

1.30 3.21 4.34 3.82 4.48 4.81 4.27 4.33 3.88 4.35 4.05

0.182 0.203 0.117 0.033 0.025 0.369 0.516 0.186 0.202 0.069 0.133

FYM = farmyard manure, CWS = chopped wheat straw, GM = green manure. bApplied at 6 t ha–1. cApplied at 3 t ha–1.

day before transplanting. The FYM and CWS were incorporated into the moist soil 2 wk before transplanting of rice. Soil samples from the 0-15 cm layer were collected periodically (1988, 1991, 1993, 1995, and 1997) after the wheat harvest. Simple linear regression analyses were done to determine grain yield trends (slopes) through the years. All the fertilizer treatments significantly improved rice yields relative to the N fertilizer control in all the years (Table 8). The highest rice yields were consistently obtained with 75% recommended NPK plus 25% N replaced by GM, which was comparable with 100% NPK, or when 50% N was replaced by GM. Rice yields with 25 or 50% of the recommended N coming from FYM were (P <0.05) lower than with 100% NPK or when supplemented with GM, only in the first 5 years. Organic sources, except FYM, applied to rice had little impact on the subsequent wheat crop (Table 8). Replacement of 50% N with FYM for rice consistently produced the highest wheat yields, which were significantly higher than wheat yields produced by 100% inorganic N applied to rice, indicating a positive residual effect of FYM. Simple linear regression analyses of rice yield from 1984 to 1997 showed significant (P <0.05) downward trends of 0.07–0.13 Mg ha–1 y–1, except in the control for which the yield decline (0.05 Mg ha–1 y–1) was not significant. Wheat yields were more stable. Significant (P <0.05) declining trends in wheat yields were ob-

served only with the applications of 75% and 100% NPK fertilizer. Total productivity (rice + wheat) declined by 0.10–0.17 Mg ha–1 y–1 over 14 years. Total soil C was maintained in all the treatments except FYM where it increased by 0.18 g kg–1 y–1 (Fig. 9). On the other hand, total soil N content significantly (P <0.05) declined with time in the nofertilizer control, 100% NPK, and GM treatments, but did not change significantly in the FYM and WCS treatments. The rate of N decline ranged from 0.01 g kg–1 y–1 in the control to 0.03 g kg–1 y–1 in the NPK treatment. The contrasting C and N trends resulted in an increase in C/N from 6–7 to 8–10 during 14 years of continuous cropping (Fig. 9). While the gradual depletion of one or more nutrients may have collectively contributed to the yield decline, the depletion of total soil N may have played a major role in the observed yield trends in this experiment. More stable wheat yields appeared to be due to continuing varietal improvement resulting in higher harvest index. Though available P and K supply could be maintained for some time from the nonexchangeable soil pools and from the irrigation water, a yield decline due to reduced soil supply of P and K could eventually occur. That suggests that current fertilizer recommendations are inadequate in the long run. If similar stagnation or declining yield trends and the gradual depletion of soil nutrients occur in farmers’ fields, the sustainability of the rice-wheat cropping system will be threatened.

16

IRRI program report for 2000

Soil total C (g kg–1) 6.5 6.0 5.5 5.0 4.5 4.0 3.5 3.0 Soil total N (g kg–1) 0.95
y = -0.03*x + 0.99 R2 = 0.94* T1 T5 T6 y = 0.18**x + 3.61 R2 = 0.98**

Increasing water-use efficiency in rice culture
Technologies and policies for agricultural water savings in China D. Dawe Water policy and management in China has changed considerably since the 1970s. Agricultural and other reforms that began in 1978 compelled irrigation agencies to become less dependent on government subsidies for operating and maintenance expenses (construction expenses for new projects and major rehabilitation are still borne to a large extent by the central government). This push toward self-reliance made irrigation agencies plan irrigation to more effectively allocate and conserve water. Water pricing was also instituted. Chinese policy dictates that domestic and industrial uses of water generally receive higher priority than agricultural uses. However, the agricultural sector pays lower prices for water than the other two sectors. The price that agriculture pays for water is regulated at the provincial level, with most irrigation districts throughout a province charging the same price. The price applies to water delivered to the lowest level measuring point in the irrigation system. Below this level, farmers may be required to pay more than the regulated provincial price to compensate for conveyance losses. Prices generally increase as one moves from well-watered southern China to water-scarce northern China. The price is typically specified in terms of a quantity of rough rice, although farmers can and usually do pay in cash (based on a government-set rice price). Because the water price is fixed in terms of rough rice, water prices over the past 20 years appear to have increased in nominal terms. These increases are essentially in line with general inflation, however, so the real price of water does not appear to have increased substantially since the beginning of the reforms. Thus, the burden on farmers has not increased over time. The water fees paid by Chinese farmers are typically assessed based on the area of their farms. There is some volumetric pricing for individual farmers, but this is relatively rare and is restricted to farmers near the head of main canals. More com-

0.80

0.65
y = -0.01*x + 0.74 R2 = 0.81*

0.50

0.35 C-N ratio 10
y = 0.28*x + 5.38 R2 = 0.99**

9
y = 0.26*x + 5.32 R2 = 0.77* y = 0.22*x + 5.43 R2 = 0.83*

8

7

6 5 10 Year 15

9. Trends of total soil C, N, and C-N ratio (1988-97) in Ludhiana, India. T1 = no fertilizer, T5 = 100% NPK for rice and wheat, and T6 = 50% NPK + 6 t FYM ha–1 for rice and 100% NPK for wheat.

Irrigated rice ecosystem

17

monly, water is measured at the point of entry to an irrigation group, which might have perhaps 30 households in some irrigation systems. This is the case in the Zheng He Irrigation System (ZIS), where IRRI conducted research in collaboration with the Wuhan University of Hydrological and Electrical Engineering and the International Water Management Institute. In other irrigation systems, water may only be measured when it enters the township, which contains much larger numbers of households. The total water fee paid by the group is then pro-rated to individual farms based on area. This creates potential problems of individual farmers taking more than their fair share and passing on the costs of additional water to the group. One might expect that, holding other factors constant, the severity of this problem is directly related to the size of the group, i.e., large groups would have more problems. Future research will attempt to quantify the magnitude of the effect of group size on water consumption. The issue may be further complicated because most farmers are not aware of the specific quantitative fee they pay for water. This occurs because they pay their water fees along with other agricultural taxes, of which the water fees are only a small part. Even if they do not know the exact fees, however, farmers clearly have a qualitative understanding that the more water their irrigation group uses, the higher their fees will be. In addition to water pricing, China has also devoted substantial effort to developing new technologies that allow farmers to save water without sacrificing yield. In rice, one of the most important technologies in China is alternate wetting and drying (AWD), wherein the field is allowed to dry to a certain extent before irrigation water is reapplied. This contrasts with the traditional practice of continuous flooding. While the role of water pricing in encouraging the adoption of AWD is not clear, it is clear that many farmers have adopted some form of AWD. We surveyed two villages within ZIS to ascertain the effects of this technology on farm profitability on yield, crop management, and profitability. One village (Tuan Lin, or TL) had widely adopted AWD. The other village (Wen Jia Xiang, or WJX) had not widely adopted AWD. The surveys showed that farmers in WJX apply irrigation water when there is still standing water in their fields. Farmers

in TL use less water for irrigation in total and are likely to wait until the soil is dry before irrigating. We hypothesized that the adoption of AWD would affect the management of other inputs, but those effects appear to be minor. Nitrogen use per hectare was similar at both sites. Labor spent in hand weeding at TL was 4.4 d ha–1, compared with just 1.5 d ha–1 at WJX, suggesting that farmers using AWD compensate for the reduced water input with more labor. Although this difference is statistically significant, the magnitude of the difference does not exert an important difference on farm-level profitability. Farmers in WJX, where more water is used, spent more money on herbicides than farmers in TL, although the difference was not quantitatively substantial. Farmers in WJX had higher yields (8.5 t ha–1) compared with those in TL (7.8 t ha–1). It is possible that the lower yields in TL were due to less water consumption, but data from controlled experiments indicate no significant difference between the two water management techniques (continuous flooding and AWD). Thus, the higher yields in WJX may be due to better soil quality or factors that we did not measure. Farmers in TL received higher net returns than farmers in WJX. There were three main factors for the higher net returns in TL, one of which was lower water costs. Lower water costs in TL were partially due to less water used, but also because farmers in WJX are forced to pump some of their water (for which they paid pumping costs). Reduced labor use and less use of hybrid seeds also contributed to lower production costs in TL. Water management effects on rice-weed interactions in direct-seeded, irrigated systems M. Mortimer, J. Hill, B. Caton, and T. Foin8 Water management is the most important cultural method of weed control in rice. This is especially true in direct-seeded systems. IRRI and the University of California, Davis (UCD), collaborated on field experiments in 1998-2000 to determine if the time of initial flooding (IRRI), water depth (UCD), or drainage (both sites) affected rice-weed competition in tropical and temperate direct-seeded rice (DSR). Early drainage is sometimes done to in-

18

IRRI program report for 2000

Table 9. Rice and weed growth in two irrigated, direct-seeded experiments on the effects of time of flooding and drainage. IRRI, 2000. 1998 WS Flooding Rice yield (t ha–1) 2.6 3.4 3.4 3.5 Panicle density (no. m–2) 488 724 808 692 Weed density (no. m–2) 184 76 24 72 Weed dry mass (g m–2) 90.6 9.7 16.2 47.8 Rice yield (t ha–1) 2.5 6.0 7.0 5.5 Panicle density (no. m–2) 511 737 793 699 2000 DS Weed density (no.m–2) 574 35 16 71 Weed dry mass (g m–2) 33.1 0.6 0.4 1.4

None 7 DAS 14 DAS 7 DAS + drain

crease the efficacy of foliar-active herbicides, or to combat stand-establishment problems. The experiments at IRRI were in 1998 WS and 2000 DS. Four treatments were nonflooded (saturated) control, flooding 14 d after sowing (DAS), flooding 7 DAS, and flooding 7 DAS but drained for 48 h at about 14 DAS. IR72 was grown in a natural weed community in both experiments. In 1998, the weed flora was dominated by Cyperus difformis and Echinochloa crus-galli. Important weed species in 2000 included C. difformis, Fimbristylis miliacea, Leptochloa chinensis, Monochoria vaginalis, and Sphenoclea zeylanica. Plant samples were taken 14, 28, 42, 63, and 105 DAS in both years. Measurements included plant and tiller densities, heights, and leaf and stem dry mass (g m–2). Experiments at UCD were at the Biggs Experiment Station in 1998 and 1999. As above, rice was grown in a natural weed community with M103 in 1998 and M202 in 1999. Treatments were water depths (shallow, moderate, or deep), either continuously flooded or drained at the 3- or 6-leaf stage of rice. In 1999, a weed-free treatment was also included, using the herbicides molinate and bensulfuron-methyl. Important weed species in both years included Echinochloa oryzoides (early watergrass), E. phyllopogon (late watergrass), Scirpus mucronatus, and Heteranthera limosa, with Echinochloa spp. dominating. Plant samples were taken 14, 28, 55, and 104 DAS in 1998, and 28 and 55 DAS in 1999. Measurements included plant heights, plant and tiller densities, and leaf and stem dry mass. Leaf N fractions were analyzed by combustion (Carlo-Erba) for rice and E. oryzoides subsamples.

Results from all experiments supported the hypotheses that water depth (UCD) or time of flooding (IRRI) affects weed species compositions and rice-weed competition, and that drainage releases weeds from some of the suppressive effects of flooding. Weed densities and dry masses in the IRRI experiments were significantly higher in the controls compared with all other flooding treatments (Table 9). Although differences between the flooded treatments were not always detected, a slight trend toward lower weed dry mass was seen for flooding 7 DAS than for flooding 14 DAS, despite lower weed densities with flooding at 14 DAS. Likewise, weed densities and dry masses were greater in the drained than in the nondrained 7-DAS flooding treatment, and rice panicle densities were lower. Hence, effects on rice yields in the flooded treatments were negligible, but drainage may increase the risk of competition from uncontrolled weeds. In more competitive situations than observed here, earlier flooding may be a useful component in an integrated weed management strategy. Results also highlight the complex interaction between water management and weed species recruitment. In the 1998 UCD experiment, competition from Echinochloa spp. was greater in drained than in continuously flooded plots. Part of the reason for this was the effect of water management on canopy development, but differences in leaf N content were also found. The leaf N contents (LN) (g N m–2) of E. oryzoides were greatest in the control treatment, and although an effect was not detected, early drainage seemed to lead to a reduction in rice LN. Hence, root zone aeration may have caused root growth responses that affected LN and rice-E. oryzoides com-

Irrigated rice ecosystem

19

petition. Understanding rice-weed-management interactions, for both water and nutrients, will be important for designing more sustainable integrated weed management programs. Nitrate and pesticide contamination of groundwater under rice-based cropping systems in the Philippines B.A.M. Bouman, A.R. Castañeda, and S.I. Bhuiyan Many of the rural poor in tropical Asia live in areas where the continuous flooding of rice fields may lead to high leaching rates of groundwater contaminants. High nitrate concentrations in drinking water can cause methemoglobinemia (blue baby syndrome) in infants and stomach cancer in adults. A concentration of 10 ppm is a generally accepted maximum for safe drinking water. A general norm for safe drinking water is 0.1 ppb for single pesticides and 0.5 ppb for multiple pesticides. We analyzed nitrate and pesticide concentrations in shallow groundwater under rice-based production systems in the Philippines from 1989 to 2000. Because nitrate and pesticide buildup may be the result of their long-term use, the history of use was documented. Sample sites were the Santa Cruz River Irrigation Scheme (SCRIS) in Laguna, the Upper Pampanga River Integrated Irrigation System (UPRIIS) in Nueva Ecija, and the watershed at Magnuang, Batac, Ilocos Norte. SCRIS and UPRIIS are representative of irrigated rice-rice cropping systems, and Magnuang represents a rainfed riceirrigated upland crop system. The predominant upland crop is sweet pepper. Wells providing water for domestic use were randomly selected within the sample areas. In SCRIS and UPRIIS, the wells were 6–12 m deep, and in Magnuang they were 5–6 m deep. Monthly water samples were taken in 1989-91 and 19992000 in SCRIS and UPRIIS, and in 1994-2000 in Magnuang. All samples were analyzed for nitrate N with a detection limit of 0.1 ppm. Pesticide residues were analyzed only in SCRIS and UPRIIS in 1989-91, and at Magnuang in 1995-96. The detection limit for the 1989-91 samples was 0.001 ppb, and that for the 1995-96 samples 0.1 ppm for fungicides and 0.1 ppb for all other pesticides. Data on the use of fertilizers and pesticides were collected.

In SCRIS and UPRIIS, the use of fertilizer N increased from below 20 kg ha–1 in the mid-1960s to 80–90 kg ha–1 in the WS and 100 kg ha–1 in the DS in the mid-1990s. The mean pesticide use increased in SCRIS from about 0.3 kg active ingredients (ai) ha–1 in the mid-1960s, peaked at 1.5–2 kg ai ha–1 in the mid-1970s to late 1980s, and decreased again to about 1.4 kg ai ha–1 in the mid-1990s. The use of pesticides was about the same in the WS as in the DS. Mean pesticide use in UPRIIS increased from 0.1 kg ai ha–1 in the mid-1960s to about 1 kg ai ha–1 in the WS and 1.3 kg ai ha–1 in the DS in the 1980s. In the mid-1990s, the WS pesticide use declined to about 0.65 kg ai ha–1. No data were available for Magnuang on long-term fertilizer and pesticide use, but in the mid-1990s, mean fertilizer N use in rice was about 60–110 kg ha–1, and mean pesticide use was 0.6 kg ai ha–1. Fertilizer N and pesticide use were extremely high in sweet pepper, with values up to 446 kg N ha–1 and 6.1 kg ai pesticides ha–1. Table 10 summarizes the seasonal nitrate N concentrations in SCRIS and UPRIIS, and Figure 10 gives the monthly nitrate N concentration at Magnuang. In SCRIS and UPRIIS, mean nitrate N concentrations varied from nil to <2 ppm. Out of the 633 well samples, 295 had nitrate N concentrations above the detection limit (0.1 ppm), and only one sample was above the safe limit for drinking water (10 ppm). There was no buildup of groundwater nitrate between 1989 and 2000. In the rice-(double) sweet pepper area in Magnuang, monthly mean nitrate N concentrations varied from 5 to 12 ppm, with the highest concentrations occurring in the WS. Monthly mean values exceeded the limit in Jul, Oct, and Nov. There was no buildup of groundwater nitrate between 1995 and 2000. In the whole of Magnuang, low nitrate N concentrations (<5 ppm) in groundwater correlated with a high incidence of WS rice cultivation (>95%), whereas high nitrate N concentrations (>15 ppm) correlated with a low incidence of WS rice cultivation (<20%). Seasonal mean pesticide (residue) concentrations in domestic wells in all three areas were generally one to two orders of magnitude below the limit of 0.1 ppb for single pesticides. Of the 11 pesticides measured in SCRIS and UPRIIS, none of the seasonal mean concentrations exceeded the WHO limit in the DS, whereas, in the WS, Azin and

20

IRRI program report for 2000

Table 10. Seasonal concentrations of nitrate N in water for domestic use sampled from shallow wells in SCRIS and UPRIIS, 19882000. 1989 WS 1990 DS 1990 WS 1991 DS 1991 WS 1999 WS 2000 DS

SCRIS Wells (no.) Observations (no.) Observations > detection limit (%) Meana (ppm) Standard deviationa Maximum (ppm) UPRIIS Wells (no.) Observations (no.) Observations > detection limit (%) Meana (ppm) Standard deviationa Maximum (ppm)
a

14 42 31 0.21 0.46 2.30 – – – – – –

14 36 100 0.56 0.54 2.79 – – – – – –

– – – – – – 36 63 100 0.53 0.37 1.55

14 25 52 0.34 0.57 2.1 36 105 68 0.29 0.36 2.20

14 11 55 0.48 0.78 2.4 36 36 47 0.22 0.40 2.20

10 50 16 0.27 0.97 5.60 25 125 31 0.56 1.73 12.00b

10 40 5 0.01 0.04 0.23 25 100 27 0.14 0.29 1.70

Calculated over all data with values below detection limit set to 0 ppm. bAbove safe drinking water limit of 10 ppm.

Nitrate N (ppm) 20 16 12 8 4 0 J F M A M J J A S O N D WHO-limit

10. Monthly mean nitrate N concentration in four wells in Magnuang, Philippines. Bars are the 1995-99 means; vertical lines are the standard deviations. IRRI, 2000.

butachlor exceeded the WHO limit in SCRIS, and endosulfan exceeded it in UPRIIS. Mean concentrations of all other pesticides combined (0.046–0.248 ppb) did not exceed the WHO limit of 0.5 ppb for multiple pesticides. In single instances, however, pesticide concentrations were quite high, with maximum values reported in the WS in SCRIS of 4.170 ppb for Azin and 1.140 ppb for butachlor. In Magnuang, 20 of 22 pesticides analyzed had concentrations below the limit. There were two instances of high chlorpyrifos concentrations (1.311 and 2.0 ppb). Because the detection limit was the same as the limit for single pesticides, we do not know whether the cumulative pesticide concentration exceeded the limit. Human health was not threatened by nitrate concentrations in drinking water in SCRIS and UPRIIS.

In Magnuang, the extremely high fertilizer N use for sweet pepper caused nitrate concentrations close to, or above, the limit. Pesticide residues did generally not exceed health safety limits, except for few and occasional exceptions. For both nitrate and pesticides in wetland rice, the high leaching potential caused by the constantly percolating water may be counterbalanced by the transformation processes taking place in tropical, anaerobic soil. Urea is the main N fertilizer applied to tropical rice and a large fraction is lost through ammonia volatilization. Further ammonification and hydrolysis turn urea into ammonia, which remains the major form of N. Any nitrate present easily moves into reduced layers where it readily denitrifies and escapes as N2 and N 2O. Thus, the amount of nitrate available for leaching may be quite low. As with urea, volatilization causes a major loss of pesticides in the tropics, especially when applied on the surface of water or on wet soil. The remaining pesticides are readily transformed by chemical and microbial degradation. Therefore, a relatively small fraction of applied pesticides may leach into the groundwater. The agroecological environment and history of the areas studied suggest that our results may be characteristic of many parts of tropical Asia where rice-based cropping has intensified since the mid1960s.

Irrigated rice ecosystem

21

Improving pest management
Understanding variation in weed species responses to management in wet-seeded rice M. Mortimer Farmers frequently observe variation from season to season in emerging weed populations in wet-seeded rice. Experiments in collaboration with the Malaysian Agricultural and Research Development Institute (MARDI) tested the hypotheses that tillage practices before rice sowing determine the composition in the emerging weed flora in rice and that seasonal usage of the same herbicide interspecifically selects weed species in the residual weed flora. Conventional farmer tillage practice for direct seeding in Malaysia involves a sequence of tillage practices between rice crops. The sequence typically is dry tillage (after harvest) followed by wet tillage 10–14 d before rice sowing, and wet tillage immediately prior to sowing. Dry tillage disperses weed seeds into the soil and encourages their germination—especially volunteer rice after harvest. Wet tillage may cause a flush of weed emergence and a consequential reduction in the size of the weed seed bank if a second round of wet tillage occurs. However, for many weed species, especially Echinochloa crus-galli, burial through land cultivation induces seed dormancy, which may result in seed populations with half lives of more than 3 years. Thus, reduced tillage practices may be advantageous in controlling this weed. Two tillage regimes were tested: q conventional farmer practice of three rounds of tillage followed by land leveling by hand, and q reduced tillage with one round of early tillage and leveling. Three rice (MR84) seeding rates were compared—0 kg ha–1, 60 kg ha–1, and 100 kg ha–1, together with the herbicide regimes 2,4-D amine, quinclorac, and a nonsprayed check. Reduced tillage resulted in heavy infestation (dry weight at 60 DAS) of Fimbristylis miliacea. On the other hand, conventional tillage lowered total weed biomass but increased the proportion of broadleaf weeds especially Monochoria vaginalis. The biomass of E. crus-galli was similar with both

tillage treatments. A rice seeding rate of 100 kg ha– 1 significantly reduced sedge and broadleaf weed biomass at 60 DAS but there was no corresponding reduction in E. crus-galli. Herbicides were effective in selective weed control. However, noticeable compensatory responses occurred in other components of the weed flora when specific weed groups were chemically removed. For four commonly used herbicides, significant yield gains were initially achieved in comparison with manual weeding but the application of the same herbicide in successive cropping seasons resulted in a noticeable tendency for yield decline over four seasons. In contrast, manual weeding maintained yields at similar levels over the same period. The sole use of a broadleaf herbicide (2,4-D) rapidly selected for grass weeds (e.g., E. crus-galli), whereas graminicides alone promoted growth of broadleaf species (e.g., M. vaginalis). In addition, increased diversity of weed species occurred over four seasons, indicating the potential for further shifts in the weed flora. These results confirm the need for rotational use of chemicals in weed control to protect yields. In addition, the results emphasize the nature of the interaction between tillage and herbicide regimes in governing rice yields. Effect of Bt rice on the brown planthopper and its predator Cyrtorhinus lividipennis C.C. Bernal, R.M. Aguda, and M.B. Cohen Rice genetically engineered with toxin genes from Bacillus thuringiensis (Bt) is being developed by numerous institutions to provide resistance to lepidopterous pests such as stem borers and leaffolders. Bt toxins generally have little or no toxicity for nontarget organisms, such as natural enemies and sucking insect pests. However, it is particularly important to examine the nontarget effects of Bt rice because of the fundamental role of biological control in rice pest management. The effects of Bt rice lines on the brown planthopper (BPH), and its most important hemipteran predator, Cyrtorhinus lividipennis, were studied. We examined whether Bt toxins are present in the phloem and xylem of the rice plant (the sites of BPH feeding), compared the development and

22

IRRI program report for 2000

feeding behavior of BPH reared on Bt and non-Bt control lines, and compared the development of C. lividipennis when fed BPH reared on Bt and non-Bt control lines. The experiments were with five Bt rice lines, each with a different promoter (CaMV35S, actin, ubiquitin, trpA, or PEPC) driving expression of the Bt gene. All lines contained a synthetic cry1Ab gene, except for the actin line, which contained a cry1Ab/cry1Ac fusion gene. The optical density at 450 nm (OD450) of honeydew excreted by BPH feeding on Bt lines with the CaMV35S and actin promoters was significantly higher than that of BPH feeding on control lines, when processed with a Cry1Ab ELISA kit. This indicates that Bt toxin is ingested by BPH that feed on Bt lines with these gene promoters. In all cases, BPH feeding on Bt lines produced more honeydew derived from xylem feeding than BPH feeding on control lines. The amount of honeydew produced from phloem feeding did not differ significantly between BPH feeding on Bt and control lines. There were no significant differences between BPH reared on Bt lines and control lines for any of the five development parameters examined (percent survival to adult stage, male and female weight, and male and female developmental time). Similarly, there were no significant differences between C. lividipennis reared on BPH nymphs from Bt lines and control lines, for any of the three development parameters examined (percent survival to adult, and male and female developmental time). The detection of Bt toxin in the honeydew of BPH that fed on Bt rice lines with certain promoters indicates that BPH and its natural enemies can be exposed to toxin from Bt rice. Also, BPH on the Bt lines apparently detected the presence of the toxin and changed their feeding behavior. However the absence of effects of the Bt lines on the survival and development of BPH and C. lividipennis suggests that there will be no direct, acute effects of Bt rice on these two species in rice fields.

(NARES) and IRRI. The consortium was initiated in 1997 with funding from SDC and the first phase was completed in 2000. Phase I brought together three networks: Integrated Pest Management (IPMNet), Integrated Nutrient Management (INMNet), and the Hybrid Rice Network (HYNet), each consisting of key NARES partners, to apply knowledge for local needs in irrigated rice and to develop methods for delivery and adoption. The IRRC greatly enhanced IRRI’s partnership with the NARES, as well as increased communication and the exchange of information among NARES. The consortium was active in all of the major irrigated rice countries in the region and the IRRC Steering Committee consisted of policymakers from China, India, Indonesia, Lao PDR, Malaysia, Philippines, Thailand, and Vietnam. The consortium also enjoyed strong support from local governments and national agricultural institutions. Consortium coordination and research progress in 2000 included q Continued governance and management of the IRRC, and conduct of consortium activities as planned and approved by the IRRC Steering Committee. q Development of the conceptual approach and planning for the directions of the IRRC Phase II and submission of a proposal for the extension of funding of IRRC Phase II. q Facilitated research of the IPMNet, INMNet, and HYNet. q Continued data integration and analyses of the pest impact assessment research of the IRRC. Initial results (combined sites, India and Vietnam) were presented in the International Rice Research Conference 2000, and showed important relationships between high N use and specific pests. q Continued implementation of crop residue management research in four IRRC sites.

Irrigated Rice Research Consortium
The purpose of the Irrigated Rice Research Consortium (IRRC) is to address regional problems in irrigated rice through partnerships between the national agricultural research and extension systems

Program outlook
IRRI will implement a new Medium-term Plan (MTP) in 2001. In it, important activities of the Irrigated Rice Ecosystem Program will continue under a new program entitled Rice Productivity and

Irrigated rice ecosystem

23

Sustainability in Favorable Environments. These activities are embodied in four projects: q In Project 3, research to raise the yield barrier through improved plant types, particularly the new plant type (NPT), has been challenging. The NPTs have been redesigned for increased tillering as well as other high yielddeterminant growth patterns. New genes have been incorporated to combat tungro viruses and blast resistance. The project will continue to focus on stem borer and lodging resistance as well as on improved grain-filling capacity. Research on high-yielding hybrid rice from cytoplasmic male sterile and thermosensitive genic male sterile lines will continue with advanced breeding materials introduced to the NARES. q Through Projects 4 and 5, the Program will bring together research on nutrient, pest, and water management to enhance integrated natural resource management in rice production. Research on optimal N applications, internal nutrient efficiencies, and nutritional balance are directed toward sustainable nutrient management in intensively cropped irrigated lowlands. Studies on the constraints to nutrient supply, and the development of practical approaches through site-specific nutrient management and leaf color chart technologies will be in partnership with the NARES. Characterization of pest problems and generation of practical pest management strategies will also continue. The adoption of integrated pest management (IPM) focuses on motivating farmers through printed materials and radio. Seed health

evaluation for farmer crop management is emphasized. Water use within irrigation districts will continue to be evaluated with districtwide measurements and the development of models that can be extended across rice-producing areas. Improvement of on-farm water use will focus on land preparation, cultivation period, and weed and crop establishment in DSR grown with intermittent irrigation. q Because of the so-called looming water crisis, a new project on aerobic rice will investigate irrigation strategies, drought tolerance, and other possible water-saving technologies. This project will have initial collaboration with the Philippines and China, and in the rice-wheat systems of India. Research on water quality degradation and the development of feasible mitigation strategies will continue. Improved technologies for integrated nutrient and IPM will be introduced to farmers in partnership with NARES partners at pilot sites. A major effort is nearing the stage for large-scale technology transfer through the IRRC. The IRRC will continue to link with the NARES and other institutions to address important interdisciplinary regional problems in irrigated rice. The IRRC had an external review in late 1999 and was restructured from a few networks to several new problem-oriented workgroups linked together through an Impact Workgroup. The latter will assist in appraisals, delivery and evaluation of research and the extension of information to farmers to enhance the impact of the collaboration in research and technology adoption.

24

IRRI program report for 2000

Research programs Rainfed lowland rice ecosystem

MANAGING CROP, SOIL, AND WATER RESOURCES FOR ENHANCED PRODUCTIVITY AND SUSTAINABILITY OF LOWLAND AREAS 26 Growth and variability of rice production in eastern India 26 Improving timeliness and reducing cost of crop establishment 28 Weed communities of gogorancah rice in Indonesia 31 CROP AND RESOURCE MANAGEMENT FOR DEEPLY FLOODED AND COASTAL AREAS Adoption of rice-rice and rice-aquaculture farming systems in coastal West Bengal: determinants and impact 32 GERMPLASM IMPROVEMENT FOR RAINFED LOWLAND AND FLOOD-PRONE AREAS Germplasm for the rainfed lowland ecosystem 36 Breeding for the flood-prone ecosystem 37 Genotype by environment interactions in rainfed lowland environments 37 The role of active O2 scavenging systems in submergence tolerance 39 Inhibitory effect of ethylene on recovery of rice seedlings after submergence 40 Variety dependence of microbe-mediated nitrate supply: potential for microbial interventions to improve N use efficiency 41 Building partnership between scientists and farmers 42 32

36

VALIDATION AND DELIVERY OF NEW TECHNOLOGY FOR INCREASING PRODUCTIVITY OF FLOODPRONE RICELANDS OF SOUTH AND SOUTHEAST ASIA 44 Developments in boro rice farming 44 Identification of suitable boro varieties 45 Crop establishment 45 Nursery management 45 Crop management 45 PROGRESS OF UNREPORTED PROJECTS 46 Rainfed Lowland Rice Research Consortium 46 Facilitating technology transfer among NARES for the flood-prone rice ecosystem PROGRAM OUTLOOK 47

47

Rainfed lowland rice ecosystem

Rainfed lowland rice covers about 40 million ha and flood-prone rice covers about 12 million ha and supplies about 25% of the world’s rice production. Farmers in the ecosystem are confronted with drought, submergence, and problem soils that constrain the adoption of high-yielding modern varieties. Improvements required for crop management are increased tolerance for drought and submergence, better tolerance for poor soils, and better tolerance for biotic stresses. The Rainfed Lowland Rice Ecosystem program’s research activities are implemented in five projects— crop and resource management, germplasm improvement for rainfed and flood-prone areas, validation and adaptation of technologies through farmer participatory experiments, and facilitation of research partnership with national agricultural research and extension systems (NARES).

Managing crop, soil, and water resources for enhanced productivity and sustainability of lowland areas
This project develops information and technological options for improved crop, soil, and water management for sustainable increases in productivity and farmers’ income. It also identifies and analyzes the processes governing productivity and sustainability of crop production systems. Research covers nutrient and water management, crop establishment and weed management, and risk management. Growth and variability of rice production in eastern India S. Pandey, S. Pal, and R. Villano Eastern Indian states account for more than twothirds of rice area and more than half of the rice output in India. Growth rates were an impresive 3.07% y–1 for yield and 3.60% y–1 for production during 1982-97. That growth was not evenly distributed among different states of eastern India, however, and the effect of production growth on output variability at the aggregate level has not been investigated. This research examines the extent to which growth in output has resulted in an increase in production variability. The analysis is based on district-level, time-series data on rice area, yield, and production for 71 districts covering eastern Uttar Pradesh, eastern Madhya Pradesh, Bihar, West Bengal, and Orissa. The trends in rice yield and production are seen in Figure 1. Growth in yield during 1961-81 was negligible. During 1982-97, yield increased dramatically with the spread of modern varieties sup-

26

IRRI program report for 2000

Area (million ha), production (million t) 60 50 40 30 20 10 0
Production Yield Area

Yield (t ha–1) 2.6 2.4 2.2 2.0 1.8 1.6 1.4 1.2 1.0

Year

1. Trends in area, yield, and production of rough rice in eastern India, 1969-97.

ported by expansion of irrigation by shallow tubewells and pumps. Since the early 1980s, Uttar Pradesh and West Bengal have shown the strongest growth in production of rice, although all states registered a significant increase in this period (Table 1). The effect of production growth on variability in rice area yield and production was examined by using a 10-year moving coefficient of variation (CV), which adjusted the data for trends in mean values through time (Fig. 2). The results indicated that the CV of yield started to decline for most states after 1975-84 (Fig. 2A). The stabilizing effect was strongest in West Bengal, eastern Uttar Pradesh, and eastern Madhya Pradesh. On the other hand, the decline in yield variability has been modest in Orissa, while the yield variability showed little trend, or tended to increase, in Bihar. The moving CV of area indicates a clear pattern of increase in area instability in eastern Uttar Pradesh (Fig. 2B). The area instability in Bihar remained high throughout the period. The trend in production instability

generally mirrors that of the yield instability (Fig. 2C). Districts were classified into two groups for district-level analysis based on whether the average rice yield was below or above 2.28 t ha–1. The below-average group covered 55%, and the above-average group covered 45%, of total rice area. A large number of districts had statistically significant change in growth or variability, or both (defined as average % deviation from the trend) in rice yield and production between 1969-81 and 1982-94 (Table 2). Most of those districts had either a decrease in variability with no changes in growth rates of yield and production, or an increase in growth rate with no change in variability. The districts in the nochange category are in eastern Uttar Pradesh and those with an increase in growth rate with no change in variability are mostly in West Bengal. In contrast, growth in yield and production was accompanied by an increase in variability in Puri district of Orissa. Districts with average rice yield below 2.28 t ha–1 and districts with increased variability but no improvement in growth were mostly in Bihar. Thus the analysis of district-level data corroborated the finding at the state level as shown in Figure 2. A regression analysis examined the variation in district-level variability of yield (defined as average percentage deviation from the trend) across districts. Application of NPK fertilizer at the district level was the explanatory variable. It was used as a proxy for the adoption of modern varieties and irrigated areas because farmers tend to use more fertilizer when they have adopted modern varieties and when the area is irrigated. Dummy variables were used to account for agroclimatic differences across districts. The results show that the variability in rice yield during 1982-94 was negatively correlated with

Table 1. Growth rates (% y–1) in rice area, yield, and production in various parts of eastern India, 1961-97. Area State 1961-81 Assam Bihar Madhya Pradesh Orissa Uttar Pradesh West Bengal Eastern India 1.08** 0.26 0.79** 0.03 1.02** 0.81** 0.63** 1982-97 0.78* –0.18 0.61** 0.52** 0.43 1.11** 0.53** 1961-81 0.59** 0.79 0.40 –0.06 2.02* 0.91** 0.79 1982-97 1.81** 2.83* 1.31 2.52* 3.93** 3.81** 3.07** 1961-81 1.67** 1.06 1.19 –0.04 3.04** 1.73** 1.42** 1982-97 2.59** 2.65* 1.91* 3.04* 4.37** 4.92** 3.60** Yield Production

19 69 19 71 19 73 19 75 19 77 19 79 19 81 19 83 19 85 19 87 19 89 19 91 19 93 19 95 19 97

Rainfed lowland rice ecosystem

27

CV (%) 8 6 4 2 0 8
B A

6 4 2 0 8 6 4 2 0
19 69 -7 8 70 -7 9 71 -8 0 72 -8 1 73 -8 2 74 -8 3 75 -8 4 76 -8 5 77 -8 6 78 -8 7 79 -8 8 80 -8 9 81 -9 0 82 -9 1 83 -9 2 84 -9 3 85 -9 4 86 -9 5 87 -9 6 88 -9 7
West Bengal

C

Year
Orissa Eastern Uttar Pradesh

Bihar

Eastern Madhya Pradesh

2. Moving coefficient of variation (CV) of rice (A) yield, (B) area, and (C) production in eastern India, 1969-97.

the rate of NPK application. This indicates that where modern technology is adopted, the variability in rice yield is lower than where the traditional technology is used. Where adoption of modern varieties was supported by an assured source of irrigation, such as in eastern Uttar Pradesh and West Bengal, there was an overall decline in yield variability as well as an increase in the growth rate of yield.

Improving timeliness and reducing cost of crop establishment R. Bakker, T. Alihamsyah, and P. Borlagdan A major constraint in rainfed lowland farming systems is the provision of sufficient labor and draft power for adequate, timely farming activities, especially land preparation, seeding, and weeding for direct-seeded rice (DSR). A survey of farmers in

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IRRI program report for 2000

Table 2. Change in growth and variability in the production and yield of rice in eastern India by districts. Figures in parentheses are rice area of the group as percentage of total rice area in eastern India during 1992-94. Changes in the growth and variability are statistically significant up to 10% level. None of the districts in the low-productivity group showed significant decrease in the growth rate. Change in growth rate Decrease Change in variability (annual percentage deviation from trend) Production No change Increase Decrease Yield No change Increase

Districts with yield 2.28 t ha–1 or higher Increase Sultanpur (0.71) Raipur, Bankura, Burdwan, Darjeeling, Midnapore, Murshidabad, Purulia, West Dinajpur (18.41) Ballia, Gonda, Gorakhpur, Sahabad, Sambalpur, 24-Paragana, Birbhum, Hooghly, Malda (13.78) Puri (1.82) Gonda, Gorakhpur, Sultanpur (3.0) Raipur, Bankura, Darjeeling, Midnapore, Murshidabad, Purulia, West Dinajpur (15.77) Puri (1.82)

No change

Allahabad, Azamgarh, Faizabad, Ghazipur, Jaunpur, Mirzapur, Pratapgarh, Nadia, Varanasi, Howrah (7.70) Deoria (1.06)

Ganjam (1.47)

Allahabad, Azamgarh, Deoria, Faizabad, Ghazipur, Jaunpur, Mirzapur, Pratapgarh, Varanasi (6.88)

Ballia, Sahabad, Ganjam, Sambalpur, 24-Paragana, Birbhum, Burdwan, Hooghly, Howrah, Malda, Nadia (17.48)

Decrease

Districts with yield less than 2.28 ha–1 Increase Basti, Bilaspur, Balasore, Bolangir, Dhenkanal, Cooch-Behar, Jalpaiguri (13.04) Balaghat, Jabalpur, Raigarh, Shahdol, Surguja, Kalahandi (7.71) Durg, Mandla, Seoni, Bhagalpur, Dhanbad, Gaya, Hazaribagh, Palamau, Purnea, Ranchi, Saharsa, Santhal Paragana, Saran, Singhbhum, Cuttack, Keonjhar, Koraput, Mayurbhanj, Phulbani, Sundergarh (25.85) Bahraich, Bastar, Champaran, Darbhanga, Monghyr, Muzaffarpur, Patna (9.56) Basti (1.76) Bahraich, Bolangir, Keonjhar, Cooch-Behar, Jalpaiguri (5.95)

No change

Balaghat, Jabalpur, Raigarh, Shahdol, Surguja, Dhanbad, Kalahandi (7.92)

Bilaspur, Durg, Mandla, Seoni, Bhagalpur, Champaran, Gaya, Hazaribagh, Palamau, Patna, Purnea, Ranchi, Saharsa, Santhal Paragana, Saran, Sighbhum, Balasore, Cuttack, Dhenkanal, Koraput, Mayurbhanj, Phulbani, Sundergarh (33.34)

Bastar, Darbhanga, Monghyr, Muzaffarpur (6.05)

Rainfed lowland rice ecosystem

29

rainfed lowland areas of Central Java, Indonesia, indicated that farmers are experiencing changes in the availability and cost of rural labor and are adopting labor- and cost-saving methods. Central Java farmers prepare soil following first monsoon rains and rice is sown before fields are flooded. This rainfed lowland cultivation system is locally known as gogorancah (dry-seeded rice). Rice may germinate at the onset of the monsoon rains, but rainfall is unpredictable, planting is often delayed, and drought stress occurs at different stages of crop growth. Farmers use water buffaloes for tillage with traditional implements and planting is done by hand (dibbling) or a combination of manual labor and animal traction (furrow seeding). The traditional seeding methods are labor-intensive, require high seeding rates (up to 200 kg ha–1), and often lead to late establishment and irregular crop stand. Surface broadcasting of seed is not popular among farmers because of limited access to herbicides and sprayers to control weeds. Yield of the first DSR crop can be as high as 6 t ha–1 but yields are highly variable because of fluctuations in rainfall. Farmers may follow the first DSR crop with a second crop by soil puddling and transplanting of seedlings in an attempt to use the remaining soil moisture. Farmers in Central Java have started using simple two-wheel tractors for cultivation. The tractors are manufactured in Indonesia and often owned by farmers who offer contractual tillage services to other farmers in their village. The tractors were initially used for puddling to quickly establish the second rice crop, but farmers have gradually started using them for land preparation for the DSR crop. Mechanizing tillage at the start of the season enables farmers to start operations earlier in the season, with additional improvements in timeliness of the second crop. A case study in one village shows that the cost for mechanized tillage is lower (US$18.25–25 –1) ha than the cost for traditional tillage (US$26.50–37.50 ha–1). The availability of tractors through contract systems provides opportunities to improve the traditional methods used for direct seeding. During 1994-99, IRRI and the Central Research Institute for Food Crops (CRIFC) developed improved mechanical seeders through a farmer partici-

patory approach. The seeders, manufactured in small village workshops, mounted on the locally available two-wheel tractor and seed placement simulates the conventional DSR methods used by farmers. Animal-drawn versions of the seeders were also developed. On-station and farm-level research found that time requirements for planting were reduced from as much as 40 d ha–1 for traditional hand dibbling (five persons) and 30 d ha–1 for furrow seeding behind a country plow (four persons + one animal), down to 1.2 d ha–1 for a tractor mounted 4-row seeder (one operator + tractor). The mechanical seeding gave more uniform seeding depth and seed distribution and reduced seed rates. The best performing seeder was a simple seed drill (Fig. 3) that has tines that open slits in the soil.

3. CRIFC-IRRI seeder for rice in farmer's field, Meteseh and Rembang districts, Central Java.

Seed is deposited through a seed tube located behind the tine. Seed metering is by a simple fluted roll inside the seed hopper, which is driven by a groundwheel. Row spacing can be adjusted by changing tine spacing. The simple drill was selected by farmers on the basis of weight (implements often have to be carried to adjacent fields), ease of operation, and capacity to use it in different soil types. Estimated costs of using the tractor-mounted seeder in Central Java are $15.30 ha–1, assuming a 6-year economic life for the seeder, use for 20 d season–1, and 100 d y–1 tractor use (20 d for seeding and 80 d for other operations). This represents about half the costs of furrow seeding behind a country plow ($31.25 ha–1). A sensitivity analysis showed

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IRRI program report for 2000

Table 3. Assessment of a mechanical seeder in 20 farmers’ fields in Tawangrejo village, Blora, Central Java, 1999-2000. Farmers’ (%) rating of tractor-mounted seeder Good Ease of operation Ease of handling Ease of transporting Ease of field-to-field transfer Straightness of the row Neatness of seed drop in the row Uniformity of seed emergence Overall performance Zone C 70 80 70 70 90 90 90 90 Fair 20 10 20 20 0 0 0 10 Poor 0 0 0 0 0 0 0 0 Good 30 20 20 30 10 0 10 10 Farmers’ (%) rating of traditional furrow seeding Fair 60 70 60 50 90 70 70 70 Poor 10 10 10 10 0 10 20 20

Parameter

that the tractor-mounted seeder is competitive with the established seeding methods at utilization rates of 10 ha season–1 or more. To further evaluate the seeder’s acceptability to farmers, it was made available to farmers in three villages, and seeding in farmers’ fields was done in collaboration with local tractor owners. Responses of farmers (Table 3) confirmed that the mechanical seeder provided more even seed placement and improved plant stand. The study showed that relatively simple interventions can greatly improve the productivity and profitability of DSR. The seeder design was made available to the Indonesian Assessment Institute of Agricultural Technology to test its performance and acceptability in other provinces. Weed communities of gogorancah rice in Indonesia H. Pane9, E. Sutisna Noor9, M. Dizon, and M. Mortimer Dry-seeded rice is grown in the Jakenan region, Central Java, Indonesia, from the onset of the wet season (WS)(Oct-Nov) through Jan-Feb, followed by minimum-tillage transplanted rice (TPR) until May. Weed control in both crops is manual, with labor at 80 d ha–1 in DSR and 48 d ha–1 in TPR. Yield reductions due to weeds can be 76% in DSR and 45% in TPR. Weed communities vary in composition, are higher in DSR than in TPR, and severest in low-lying areas. Documentation of the efficacy of farmer weed control practices and of the abundance and diversity

of weeds throughout crop growth provides a baseline for an analysis of the impact of existing weed control systems and for an ex ante assessment of proposed changes in management. A study was designed to obtain a baseline as a precursor to the design of on-farm yield gap trials. The objectives were to quantitatively describe the on-farm weed flora in DSR, to analyze variation in that flora in relation to toposequence and soil characteristics, and to provide implications for improved weed management. Twenty-five farm sites were chosen in subdistricts within 50 km of CRIFC’s Jakenan station in the districts of Pati and Rembang. Three positions (upper, middle, and lower) on the sloping lands (5–30°) of the toposequence were chosen for each farm. The weed flora was assessed during Feb 1998 when rice was at the booting stage and the density of individual weed species (plants m–2) enumerated by destructive removal of all plants beyond the small seedling stage. Farmers were interviewed prior to data collection to confirm that rice weeding had been finished and to record nutrient management practices. Bulk soil samples were taken at each toposequence position, and pH, % total organic carbon, % total N, soluble phosphorus (mg kg–1), exchangeable K (meq 100 g– 1), and cation exchange capacity (CEC) (meq 100 g– 1 ) were measured. Farmyard manure was the principal source of fertilizer. Univariate analysis of variance was used to explore variation in weed densities and in soil nutrient status among sites. Weed-site associations were assessed using correspondence analysis and unimodal

Rainfed lowland rice ecosystem

31

species responses to environmental variables examined with canonical correspondence analysis. Considerable intersite variation was found in mean levels of K, P, organic C, and CEC, with the latter significantly correlated with all variables except phosphate. No differences in N status were found. Soils from upper positions were always more acid, with the average difference within a site being 0.65 of a pH unit from upper to lower position. Contrastingly, K, P, organic C, and CEC varied among sites at every farm and differences were not correlated with toposequence position. Levels of nutrients fell within reported ranges for other rainfed lowland environments. The sites were characteristically nutrient-deficient. Species commonly observed in the flowering stage were Eclipta alba, Echinochloa crus-galli, E. colona, Fimbristylis miliacea, Cyperus difformis, and C. rotundus. The overall mean total weed density was 175 plants m–2, which did not differ significantly in relation to toposequence when averaged across sites. Figure 4 shows the predicted distribution of six major weed species in relation to toposequence. The study showed that surprisingly dense, diverse weed communities persisted in DSR during the later stages of crop development. Their presence may reflect the fact that farmers perceive little economic benefit in weed removal at late stages of crop development, particularly because manual weeding may damage the crop. However on-farm yields have been reported as typically less than 3 t ha–1 in contrast to yields of weed-free research station trials of 3 and 5 t ha–1 depending on water availability and nutrient management. The 30-d duration between last weeding and crop harvest is sufficient for populations of E. colona, F. miliacea, and Lindernia spp. to develop, and for species with strong developmental plasticity (e.g., Ammania baccifera) to complete their life cycle and to pose a competitive threat (for light and nutrients) to yield during grain filling. The weed diversity in the ecosystem also implies the strong potential for transient, longer term shifts in relative abundance of weed species in response to changes in agronomy and water management and herbicide use. The existence of grass weeds such as E. crus-galli, Leptochloa chinensis, and Ischaemum rugosum, and of C. difformis clearly poses a signifi-

cant threat to rice intensification and underlies the importance of effective early weed control.

Crop and resource management for deeply flooded and coastal areas
Productivity of deeply flooded and coastal areas depends on the combination of cultural methods and selection of suitable crops. Research focus for 2000 was on the productivity, sustainability, and the environmental impacts of the emerging farming systems. Adoption of rice-rice and rice-aquaculture farming systems in coastal West Bengal: determinants and impact M. Hossain, S.K. Bardhan Roy, N.K. Saha, and F. B. Gascon One-fifth of the net cultivable area of India’s West Bengal state is in the coastal region. Salinity and flooding are main constraints to agricultural production. The coastal area has traditionally grown rainfed rice monocropped with photoperiod-sensitive, long-duration, low-yielding varieties. Substantial changes in land use have occurred in the last decade due to the availability of modern rice varieties and small-scale irrigation, a growing knowledge of semi-intensive shrimp and prawn culture, and a strong market for fish and shrimp at home and abroad. There has been an increase in adoption of ricerice and rice-aquaculture farming systems but there is inadequate information on these emerging farming systems. Furthermore, there has been concern that the rice-aquaculture farming system, which uses brackish water in the dry season (DS), may lead to increased soil salinity and toxicity. That could make land unsuitable for both rice cultivation and aquaculture in the long run. A study of the farming systems sought to q document the farming systems practices at different levels of soil salinity and land forms, q analyze the determinants of adoption of the emerging farming systems, and q assess the overall impact of rice-aquaculture and other farming systems on farmers’ income and sustainable management of natural resources.

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IRRI program report for 2000

The study included 18 sample villages in four coastal districts representing different levels of soil salinity and natural resource management practices in West Bengal. We used focus group discussions with village leaders to collect information on the land use pattern, ecosystem characteristics, infrastructure facilities, farming practices, prices of agricultural inputs and outputs, terms and conditions of tenancy, and labor market. One hundred and seventy-nine households (10% of the total households) in the villages were selected for an in-depth household survey. The survey data consisted of q socioeconomic background of the household, farmers’ perception of the biophysical characteristics (salinity, flooding depths, elevation) of different parcels of land owned and operated by the household; q utilization of the parcels in different seasons; q inputs used and production for different enterprises; and q farmers’ perceptions regarding the sustainability of the emerging farming systems. Secondary information on changes in the farming system was also collected from various local organizations and from unpublished documents. Multivariate regression models were used to analyze factors affecting the adoption of rice-rice and rice-aquaculture farming systems, the effect of the new farming systems on the yield of aman (WS) rice, and the impact on sustainability of the system. The survey identified three major land use patterns (Table 4). The rice-based system was found to be significantly higher across the salinity level. A nonrice based cropping system was practiced in nonsaline to moderate-saline areas. Although a
Table 4. Distribution of area (%) by land use system and salinity level in 18 villages in four coastal districts. West Bengal, India, 2000. Salinity level Land use system Non-saline Rice-based Nonrice-based Noncrop-based Homestead and fallow Total
a b

Moderate 69.6 7.8 14.9b 7.7 100.0

Severe 56.0 0.0 40.0c 4.0 100.0

63.4 7.4 12.9a 14.3 100.0

Mostly vegetables and spices and orchards in the homestead. Mostly pulses, oilseeds, and spices. cMostly fish.

noncrop (aquaculture)-based system was practiced across different salinity levels, it was significantly higher in severe saline areas than in other salinity levels. Single-cropped rice occupied a major part of moderate-saline areas. Rice-rice systems were adopted in 27% of the area, mostly on land of medium flooding depth and moderate soil salinity. Among the noncrop-based system, rice-aquaculture accounted for 7% of the surveyed area. Nearly 15% of the parcels with severe salinity were used for salt making, and another 14% for raising fish. Focus group discussions revealed that the shift from rice-fallow to rice-rice and rice-aquaculture, although started in the 1970s, occurred between the mid–1980s and early 1990s. The shift had taken place on 41% the total land area. Table 5 indicates that there is a higher probability of adopting the rice-rice system if the parcel has access to irrigation, is situated in the medium elevation with lower depth of flooding, and has clay soil instead of loamy or sandy soils, which require more irrigation and increase the cost of cultivation of DSR. The probability of lower adoption at higher levels of moderate soil salinity affects the adoption of the system. This suggests that availability of moderate salinity-resistant rice varieties and the development of irrigation management practices that preclude intrusion of saline water during the critical stages of crop growth have been effective in inducing farmers to grow another rice crop during the DS. It is interesting to note that variables representing farm size and the availability of credit and educational status of the farmers have negative signs, and all coefficients are statistically significant. That shows the smaller and less educated farmers are adopting the intensive rice system faster than larger, better educated ones, and the availability of finance is not a constraint to the adoption of the rice-rice system. It is presumably subsistence pressure that is inducing farmers to adopt rice-rice, and the amount of investment needed for growing modern varieties is not high enough to preclude cash-starved farmers from doing so. The most important variable affecting the adoption of the rice-aquaculture systems is the soil salinity of the parcel and the depth of flooding. There is a higher probability of adopting the system if the soil is highly saline and of loamy or sandy type, and

Rainfed lowland rice ecosystem

33

Table 5. Factors affecting adoption of rice-rice and rice-aquaculture cropping patterns. Regression analysis of data from 179 households. West Bengal India, 2000. Mean values of the variables 1.02 0.87 1.21 Rice-rice system (n = 112) –.46** (–3.80) –0.20* (–2.18) –0.42* (–2.18) 1.61** (8.55) 0.46* (2.44) –0.18 (–0.63) 0.59 (1.81) 0.74* (2.68) –0.72** (–3.68) –1.07** (–3.49) 137 –233 Rice-aquaculture system (n = 78) 0.26** (2.56) –0.005 (–0.006) 0.30 (1.65) –0.80** (–3.69) –0.096 (–0.47) 1.383** (5.44) –0.376 (–1.25) –0.592* (–2.23) 0.40* (2.08) –0.78** (–2.68) 93 –147

Factor Farm size Education ha

Unit

Access to credit Irrigation Moderate salinity Severe salinity High elevation Medium elevation Loamy soil Constant Chi-square Log-likelihood ratio

Illiterate = 0 Primary = 1 Secondary = 2 Yes = 1 No = 0 Irrigated = 1 Rainfed = 0 Yes = 1 No = 0 Yes = No = 0 Yes = 1 No = 0 Yes = 1 No = 0 Yes = 1 No = 0

0.28 0.37 0.59 10.14 0.16 0.72 0.29 -

the parcel is at a low elevation with high depth of flooding. Such parcels are not suitable for growing rice during the DS (rice-rice system). Among the socioeconomic variables, only farm size has a statistically significant association with the adoption of the rice-fish system; the positive value of the coefficient indicates that it is the larger farmers who adopt the system more than the smaller ones. The findings on the costs and returns of the major cropping systems are reported in Table 6. Farmers in the rice-rice system got about 85% higher value of production than farmers in the traditional rice-fallow system. But, the cost of inputs was nearly four times higher for the rice-rice system compared with the rice-fallow systems. The cost of hired labor was, however, proportionately lower than the increase in outputs because of the greater use of family labor during the DS, which is a slack time for agricultural activities. The total paid-out cost was 64% of the gross value of production for the rice-rice system compared with 55% for the traditional rice-fallow system. The family income ha–1 of land was US$185 for the rice-rice system and US$125 for the rice-fallow system.

The yield of rice in the rice-aquaculture system was lower (19%) than the yield in the rice-fallow system, but the farmer got an additional 477 kg of fish and shrimp ha–1, of which 75% was shrimp, which fetched a premium price in domestic and inTable 6. Cost and returns a for different cropping patterns incoastal areas of West Bengal, 1995-96. Ricefallow Ricerice Riceaquaculture

Yield (kg ha–1) Rice Shrimp Fish Costs and returns (US$ ha–1) Gross value of output Current inputs Seeds or fingerlings Fertilizer and lime Pesticides Irrigation cost Fish meal Taxesc Hired power Hired labor Total cost Net income
a

2,229 – – 280 36 21 13 2 1 – 2 9 108 155 125

4,125 – – 524 481 23 57 18 50 – 6 28 153 336 188

1,815 360 117 2,279 1,175 1,162 10
b b

19 27 3 42 1,263 999

Weighted av of WS and DS. bLess than US$1.00. cIncludes rent paid for land.

34

IRRI program report for 2000

ternational markets. The gross value of production in the rice-aquaculture system was about eight times higher than the rice-fallow system, and 4.4 times higher than the rice-rice system. Shrimp cultivation, however, requires high investment. The cost of fingerlings was US$1,140 ha–1 compared with the seed cost of only US$21 ha –1 for rice cultivation. Because the farmers practiced traditional (semi-intensive) shrimp cultivation, the cost of fish meal was much lower than the cost of irrigation and fertilizer for the cultivation of the DS rice. The use of hired labor in the riceaquaculture system was also lower than for the ricefallow or rice-rice system. This finding suggests that the landless and the marginal landowners who supply labor in the market do not gain much from this emerging system. The net family income for the farmer from the rice-aquaculture system was estimated at US$1,000 ha–1, nearly four times of the income from the ricerice system and 10 times the income from the traditional rice-fallow system. The land productivity and family incomes from the adoption of riceaquaculture were positively associated with soil salinity.

Due to the high cost of inputs in the riceaquaculture system, small landowners often lease their land (sometimes collectively) after the rice harvest to landowners or outsiders interested in aquaculture during the DS. The rent received for this seasonal tenancy varied from US$143 to US$214 ha–1,which was higher than the net family income from the cultivation of the DS rice, or alternative economic activities that land owner could have pursued. Thus the tenancy system for aquaculture farming also provided benefits to the small landowners who are constrained from taking up aquaculture due to lack of capital. But the benefit accruing to the aquaculture farmers (who belong to the high-income group) was much larger, suggesting that the emergence of the riceaquaculture system has accentuated the inequality in the distribution of rural income. Table 7 shows the results of analysis of the effects of various parameters of the rice-rice and riceaquaculture on the yield of the aman rice crop. The major factor affecting the rice yield was the use of modern varieties (MV BORO). The yield level was higher in the low-lying parcels (LOW LAND), which are regularly silted by flooding and hence

Table 7. The effect of rice-aquaculture and rice-rice farming system on WS (aman) rice yield. Regression estimates with parcel-level data from 179 households, West Bengal, India, 1995-96. Explanatory variablea LABOR FERTILIZER MV BORO CLAY SALINITY 1 SALINITY 2 HIGH LAND LOW LAND RICE-RICE RICE-AQUACULTURE 1 RICE-AQUACULTURE 2 RICE-AQUACULTURE Constant R2
a

Unit

Regression coefficient –0.005 0.53 373 59 –15 –51 53

Estimated T value –0.05 1.61 6.26 1.50 –0.72 –0.72 0.99

Significance of T 0.963 0.108 0.000 0.135 0.737 0.475 0.324

days ha–1 kg ha–1 MV=1; TV= 0 Clay soil = 1; Others = 0 Moderately saline =1 Others = 0 Severely saline = 1 Others = 0 High elevation = 1 Others = 0 Low elevation = 1 Others = 0 Rice-rice cropping = 1 Others = 0 Rice-aquaculture cropping = 1 Others = 0 Rice-aquaculture sequence = 1 Others = 0 Years rice-aquaculture system in production

253 –219 –35 –50 8 0.78 0.26

3.69 –3.42 –0.36 –0.73 1.24 12.8

0.000 0.000 0.729 0.468 0.216 0.000

The dependent variable is rice yield in the aman-season (traditional crop) measured in kg ha–1.

Rainfed lowland rice ecosystem

35

more fertile. The yield was positively related with fertilizer use (FERT), and was relatively higher on clay soils (CLAY), presumably because of higher moisture-holding capacity. The rice-rice system has a negative effect on yield as shown by the negative and the statistically significant coefficient of the variable representing parcels that were used for growing DS rice (BORO) before the cultivation of aman rice. However, no significant relationship was found between the rice yield and the number of years the farmer had been practicing riceaquaculture system in the parcel (YEAR) or whether the farmer had been growing fish in the parcel as a mixed crop with rice (MIXED). The indirect analysis with cross-section parcel-level data thus fails to validate the hypothesis that the riceaquaculture system has had adverse impact on soil quality and rice yields. Because salinity status will determine the sustainability of the changing farming system, further study with actual measurement of soil characteristics is suggested. Development of salinity-tolerant varieties, improved management practices for rice-aquaculture system, early maturing rice varieties for the rice-rice system, and management options for irrigation and drainage were identified as the major technological needs of the farmers.

Germplasm for the rainfed lowland ecosystem S. Sarkarung and R.K. Singh Thailand. The elite line, IR62558-SRN-17-2-1-B, was released as Surin 1 for drought-prone conditions in northeastern Thailand in 2000. This variety combines resistance to blast and bacterial blight and tolerance for salinity. Because it is insensitive to daylength, farmers can grow it in the DS. Its grain quality is suitable for industrial use. This is the first nonglutinous variety ever released from the Thailand-IRRI shuttle breeding program. A total of 12 advanced breeding lines have been evaluated in farmers’ fields in northeastern Thailand (e.g., Ubon, Surin, Nakorn Ratchsima, Sakon Nakorn, and Khonkaen). The most promising lines were IR68796-27-3-B-6-1-B and IR69515-27KKN-1-UBN-1-1-1-B. In drought-screening tests, these lines showed high drought resistance at the vegetative stage. India. A release proposal for IR66363 (NDR96005) was submitted to the government of Uttar Pradesh, India. The variety did well in on-station and on-farm trials with yields ranging from 3 to 5 t ha–1. It has adequate submergence tolerance and tolerates delayed planting, making it suited to the rainfed lowland ecosystem. Farmers in submergence-prone areas in eastern India are frequently forced to delay transplanting due to late onset of monsoon rains. The breeding lines IR66366-M-7-1-1-1-1, IR66876-11-M-1-1-1, and IR67471-8-M-1-1-1-1 exhibit low yield losses due to delayed transplanting. The promising line, IR67493-M-2 (NDR 8002), designated as IET15848 in the slender grain trials of the All India Coordinated Rice Improvement Program (AICRIP) since 1997, was recommended for release for semi-deepwater ecosystems (40-70 cm) in Orissa, West Bengal, eastern Uttar Pradesh, and Madhya Pradesh. It has grain quality similar to PR106 and is resistant to whitebacked planthopper and moderately resistant to blast. The line IR54112B2-1-6-2-2-2, which has high submergence tolerance has been nominated for the same ecosystem in West Bengal and Orissa. The lines SBIR66366-7-M-1-1-1-1, SBIR66876-11M-1-1-1, SBIR69051-M-1-1-1-1-1, SBIR67471-M-8-11-1-1, SBIR67051-15-M-1-1-1-1, and SBIR67471-M-9-

Germplasm improvement for rainfed lowland and flood-prone areas
Germplasm improvement for the rainfed lowlands is complicated due to the heterogeneity and complexity of the environment. A breeding program based on physiological understanding of plant adaptation and environmental characterization operates through a shuttle breeding partnership in collaboration with NARES at key representative sites. A methodology for field evaluation of genotype by environment (G × E) interaction was developed, and preliminary analysis identified principal factors influencing G × E interaction. An important constraint to adoption of improved germplasm that tolerates drought and submergence is the preservation of traits found in traditional cultivars that are highly valued by farmers and consumers. This constraint is approached through farmer participatory breeding and selection of advanced lines based on indigenous knowledge of farmers.

36

IRRI program report for 2000

1-1-1-1 were nominated to AICRIP from 1997 to 2000 and are at different stages of testing. Five advanced lines were nominated for the AICRIP 1999 Initial Variety Trial for Shallow Water: TTB522-SBIR70237-3-1 (IET16679), TTB532-SBIR70197-23-2 (IET16680), TTB528SBIR70251-15-2 (IET16681), TTB517-44SBIR70149-33-1 (IET16682), and TTB517-44SBIR70149-33-2 (IET16683). A few of them were promoted to the next stage of testing. Philippines. The elite line IR54068-B-60-1-3-3, designated as PSBRc 102, was recommended for release in drought-prone environments of Central Luzon, Philippines. It is resistant to bacterial blight, brown planthopper (BPH), BPH biotype 1 (BPH1), and moderately resistant to BPH2, BPH3, and green leafhopper (GLH). It has long slender grain with 23% amylose content. Breeding for the flood-prone ecosystem G.B. Gregorio, R. Mendoza, A.N. Monroy, and P. Bonilla Three hundred and twenty-eight elite breeding lines were generated from crosses between high-Fe rice parents and modern varieties. These Fe- and Zndense rices will be distributed for NARES field tests in the Philippines, Vietnam, Bangladesh, and Indonesia. Three important quantitative trait loci (QTLs) were detected for the high grain-Fe trait. These are located on chromosomes 7, 8, and 9. A double haploid population of IR64/Azucena was used to map those QTLs. Simple-sequence repeat (SSR) markers RM09 and RM24, flanking the salinity tolerance genes on chromosome 1, were identified. These markers will be tested in breeding populations to confirm their applicability for marker-aided selection for salinity tolerance. Genotype by environment interactions in rainfed lowland environments L.J. Wade and C.G. McLaren The nature of G × E interactions in rainfed lowland rice was examined from 1994 to 1997 using data for 37 genotypes across 36 environments in India, Bangladesh, Thailand, Indonesia, and the Philippines.

More than 47% of the G × E sum of squares was captured by nine genotype groups and nine environment groups. Sites with similar characteristics were tightly grouped, as were related genotypes. Environment groups included some with favorable water supply, and others with early drought, late drought, rapid-onset late drought, and submergence. Groupings of genotypes could be explained by their performance in relation to those conditions (Fig. 5). Genotype groups 74 and 85 comprising varieties and hybrids with high yield potential, semidwarf stature, and short duration (90-95 d) yielded well in favorable environment groups 60-61, but yielded poorly when subjected to drought (groups 62 and 46) or submergence (group 63). Genotype group 76, including the reference line IR62266-42-6-l, showed tolerance for late-season drought, but not for flooding. Groups 81 and 79, typified by CT9993-5-10-1-M, which flowered at 100 d, and Mahsuri, which flowered at 110 d, were stable in yield across most environments. Group 52 (NSG19) was preferentially adapted to environments with rapid-onset late drought, and group 82 (Sabita and KDML 105) to environments favoring late maturity or recovery after drought. A reference set of nine lines was identified— Sabita, NSG19, IR58821-23-1-3-1, Mahsuri, IR52561-UBN-1-1-2, CT9993-5-10-1-M, IR62266-426-l, PSBRc 14, and CT9897-55-2-M-3M. They represent broad and specific adaptations to the major target subecosystems in the rainfed lowlands. G × E interactions were also examined for phenology, biomass, yield components, and drought measures. Flowering date, as a measure of phenology, and plant height, as a measure of relative biomass, showed little G × E interaction, but were important in explaining grain yield. Flowering date and plant height were both negatively correlated with yield interaction scores, indicating that the taller, long-duration cultivars (the more traditional, photoperiod-sensitive lines) showed positive yield interaction in stress sites and were disadvantaged in favorable sites in comparison with the modern cultivars. The number of days from onset of late-season drought until physiological maturity at sites with lethal late-season drought was used as one measure of drought tolerance. It showed a strong, nonlinear relationship with G × E interaction in grain yield, leading to a partitioning of genotypes into three

Rainfed lowland rice ecosystem

37

Response patterns Sabita KDML 105 IR57546-PMI-1-B-2-2

GGP-82

NSG 19 GGP-52

GGP-78

IR58821-23-1-3-3 IR66469-17-5-B IR66516

GGP-79

MAHSURI IR66883

GGP-84

IR52561-UBN-1-1-2 IR54071-UBN-1-1-3-1 IR57515-PMI-8-1-1-S IR66506-5-1-B IR66879 IR66883 IR20 CT9993-5-10-1-M IR66893-5-2-B IR58307-210-1-2-3-3 IR54977-UBN-6-1-3-3 IR57514-PMI-5-B-1-2 IR62266-42-6-1 IR63429-23-1-3-3 IR66882-4-4-B PSBRc14 IR64 IR36 CT9897-55-2-M-3-M IR64615H IR68877H Environment group 63 46 62 57 60 61 10 16 21

GGP-81

GGP-76

GGP-74

GGP-85

General hydrology

Stagnation Rapid onset late drought Severe rapid onset late drought Favorable (gogorancah) Favorable (long season) Mild late drought Early drought and severe late drought Prolonged late drought Submergence

5. Interaction response patterns for grain yield for nine genotype groups over nine environment groups. Response values are averages, over group members, of mean polish interaction values with a range of –3 to +3 for each genotype group. IRRI, 2000.

38

IRRI program report for 2000

Drought interval (d) 30
Sabita Mahsuri KDML 105 IR66879x4 IR665’6x3

IR66883x4

25

22
NSG19

IR20

20

15 –1.0

IR64

IR36

–0.5

0.0

0.5

1.0

Yield interaction score on PCA axis 2 6. Number of days from onset of lethal, late-season drought to physiological maturity (drought interval) against grain yield interaction scores for the second PCA interaction axis. IRRI, 2000.

groups (Fig. 6). One group, which included the irrigated lines IR64, IR36, and IR20, as well as NSG19, had short tolerance intervals and positive interaction in sites with no late-season drought. A second group with long tolerance intervals, including the photoperiod-sensitive cultivars, had positive interaction with the light-textured sites in northeast Thailand. A third group with long tolerance intervals comprised test lines with positive interaction in stressed sites but negative interaction in sites with no late-season drought. Grain size and percent filled spikelets showed strong G × E interactions that were related to interaction in grain yield. Mahsuri, which had the smallest grains of all lines tested, showed positive interaction for spikelet fertility at the favorable Philippine sites, but negative interaction at stressed sites. On the other hand, Mahsuri showed negative interaction for 1,000 grain weight at the Philippine sites. High-yield-potential cultivars IR36, IR64, and PSBRc 14 showed the opposite relationships, indicating alternative adaptation strategies. The examination of G × E interaction for yield and yield components indicated there were different strategies of cultivar adaptation across rainfed lowland environments. The use of G × E analysis on measures of phenology and drought tolerance aided the interpretation of these cultivar responses and

improved the understanding of mechanisms and traits likely to confer an adaptive advantage in specific subecosystems. It is important to clearly identify target environments and to know how well actual test environments represent those targets. A methodology for using measurements on a set of reference lines to classify sites was developed and tested. Strategies for choosing reference lines, classifying new sites, and deducing their environmental characteristics were examined. The results showed that the reference set was able to capture repeatable G × E patterns, provided it contained representatives of all discriminatory genotype groups. The methodology for characterizing new environments on the basis of reference line responses relied heavily on an ability to impute missing values. Although no optimal solution was available, a heuristic solution with the pattern analysis algorithm was satisfactory. Reference lines should be chosen according to how well they match the discriminatory pattern of their genotype group, their agronomic features, knowledge of their physiological responses, and practical issues such as the availability of seed. Based on this analysis, we conclude that a series of small field trials at many sites could obtain a useful characterization of new environments and allow breeders to appropriately weight responses of test lines. If detailed physical and climatic measurements are also made in these environments, the responses can be integrated with geographical information, physiological understanding, and crop modeling to quantify environment frequency, predictability, repeatability, and risk. The role of active O2 scavenging system in submergence tolerance E. Ella, O. Ito, and A. Ismail Active O2 species like hydrogen peroxide (H2O2) can cause dysfunction of enzymes and oxidative damage to lipids producing toxic malondialdehyde (MDA) and damaging cell membranes. Fourteen-day-old seedlings of submergence-tolerant (FR13A) and -susceptible (IR42) rice cultivars were submerged for 6 d and allowed to recover under low (300 µE m–2 s–1) or high (1,000 µE m–2 s–1) light intensities from 0600 to 1800 daily. Leaf samples for chemical analyses were collected during the

Rainfed lowland rice ecosystem

39

NADPH (µM oxidized mg–1 protein min–1) 100
FR13A

Value of SPAD meter 40
A

75

30 20
IR42

Y=19.395X + 1.454 r = 0.86

50

25

10 0 0

0 Low High
21 21

Low

High

0.5 1.0 1.5 Total ascorbate content (mg g–1FW)

2.0

7. Activity of glutathione reductase (GR) enzyme of nonsubmerged ( ) and submerged ( ) rice cultivars. IRRI, 2000.

Total ascorbate content (mg g–1 FW) 2.0
B

recovery period. Under high light intensity during recovery, FR13A and IR42 had comparable H2O2 content. However, FR13A had less MDA than IR42 under both light intensities. Among the four active O2-scavenging enzymes studied (ascorbate peroxidase, catalase, glutathione reductase [GR]), and superoxide dismutase), only the level of GR activity is significantly different between the two cultivars with higher activity (Fig. 7). The level of ascorbate antioxidant was also higher in submergence-tolerant FR13A (Fig. 8). The high levels of ascorbate antioxidant and GR activity ensure a better functioning of the ascorbic acid-glutathione cycle in FR13A. H2O2 is detoxified more efficiently in this cycle, thereby lowering the extent of exposure of membrane lipids to high levels of H2O2 and alleviating oxidative damage. This explains the difference in MDA content between these two cultivars that had comparable H2O2 production. Our results suggest the involvement of an active O2-scavenging system during recovery of submerged rice seedlings.
AsA (% of AsA + DHAsA) 100
FR13 IR42

1.6 1.2 0.6 0.4 0 0 0.05 0.1 0.15 0.2 0.25
Y=4.858X + 1.805 r = 0.93

Malondialdehyde content (nmol g–1FW)
–1 Malondialdehyde content (nmol g FW) 0.25

C

0.20 0.15 0.10 0.05 0 0
Y=0.0023X + 1.2536 r = 0.98

10 20

30 40 50 60 70 80 90 100 110 Percentage survival

75 50 25 0 Low High Low High
8. Ascorbate content (% of the total) of nonsubmerged (filled bars) and submerged (unfilled bars) rice cultivars after 4-d light treatment during recovery.

9. Association of (A) chlorophyll content after 8 d of submergence and total ascorbate content after 3 d of recovery, (B) malondialdehyde (MDA) and ascorbate content after 3 d of recovery, and (C) MDA and percentage survival after 3 d of recovery. IRRI, 2000.

Inhibitory effect of ethylene on recovery of rice seedlings after submergence N. Kawano, E. Ella, O. Ito, Y. Yamauchi, K. Tanaka, and A. Ismail Earlier studies have documented the accumulation of ethylene during submergence, causing chlorosis

40

IRRI program report for 2000

and decreasing the photo protection of the photosynthetic system. Ascorbic acid is synthesized in plants from glucose produced during photosynthesis and serves as an antioxidant or a cofactor in the xanthophyll cycle. This may play an important role in enhancing photo protection. We attempted to clarify the role of ethylene in recovery of submerged rice seedlings using AgNO3, an ethylene antagonist. Submergence-tolerant BKNFR76106-16-0-1-0 and submergence-intolerant Mahsuri and IR42 were used. Fourteen-day-old rice seedlings were sprayed with AgNO3 1 d before complete submergence for 8 d. They were then allowed to recover for 7 d after submergence. A significant decrease in ascorbic acid was observed in all cultivars during submergence, with greater reduction for the submergence-intolerant cultivars. Reduction in ascorbic acid during submergence may have decreased photo protection and slowed recovery of rice seedlings after submergence. Treatment with AgNO3 decreased stem elongation and improved survival of the susceptible cultivars but had no effect on the tolerant cultivar. Ethylene-induced stem elongation probably depleted the carbohydrates needed to provide energy for survival and maintenance processes. Chlorophyll content was positively correlated with total ascorbate content (r = 0.86; Fig. 9A). A strong negative correlation was observed between lipid peroxidation and total ascorbate content (r = –0.93; Fig. 9B) and with percentage survival (r = –0.98; Fig. 9C). Treatment with AgNO3 was, therefore, associated with suppressed chlorophyll degradation during submergence. It increased ascorbate content in the submerged seedlings during recovery of susceptible cultivars but had no effects on the tolerant cultivar. Our results suggest strong inhibitory effects of ethylene on the recovery of rice seedlings after submergence. Variety dependence of microbe-mediated nitrate supply: potential for microbial interventions to improve N use efficiency A.M. Briones and W. Reichardt Fluctuating redox potentials influence soil nitrate supply in rice cropping systems exposed to drought and flooding. This depends on the activity of aerobic, ammonium-oxidizing (nitrifying) bacteria (AOB). Therefore N uptake efficiencies of drought-

tolerant rice varieties can be viewed as a function of nitrate supply by root-associated AOB. The oxidized microenvironment of rice roots ensures the activity of root-associated AOB. Hence, the impact of AOB on fine tuning of the nitrate supply under changing redox conditions would ultimately depend on the diversity of substrate kinetic types among the ammonium-oxidizing populations. Sequencing of cloned fragments of the functional gene amoA revealed fundamental varietyspecific differences of AOB types associated with drought-tolerant rice. Ninety-six percent of polymerase chain reaction (PCR)-amplified, cloned amoA from the root environment of Mahsuri represented Nitrosospira-like sequences, which are frequent in N-limited soils. Only 85% of amoA sequences from the ammonium-rich root environment of IR63087-1-17 represented Nitrosomonas-like populations. This latter AOB population went almost undetected when using viable counts or PCR for AOB-specific 16S rRNA. 15NH Cl oxidation rates in the rhizosphere of 4 Mahsuri and IR63087-1-17 suggested an association of these rice varieties with different kinetic types of ammonium oxidizers (Fig. 10). Predominance of AOB showing adaptation to high N and low N levels seemed to match the presumed ecological niches of the varieties IR63087-1-17 and Mahsuri. This first evidence of variety-specific, root-associated microflora governing nitrate supply in the
Cumulative N uptake (mg N plant–1) 25 20 15 10 5 0 25 20 15 10 5 0 0 3 6 Days after 15N application 9
15NH + 4 15 NO3–

A

B

10. Cumulative uptake of 15N by drought-tolerant rice varieties Mahsuri (A) and IR63087-1-17 (B). IRRI, 2000.

Rainfed lowland rice ecosystem

41

rhizosphere of rice provides clues to the regulation of nitrate supply and hence of N uptake efficiencies in drought-adapted rice varieties. This may lead to the identification of options to manipulate root-associated, AOB, or genes in order to increase N use efficiencies. Building partnership between scientists and farmers T. Paris, R.K. Sahu10, V.N. Sahu10, R.K. Singh, S. Sarkarung, K. McAllister11, and M.L. Sharma10 A farmer participatory breeding project was established in eastern India in 1997 as a collaborative project among plant breeders and social scientists at IRRI and in six national agricultural research institutions. The objectives were to develop and test a methodology for effectively involving farmers in the breeding program, to improve understanding of male and female farmers’ criteria for selecting spe-

cific rice varieties, and to develop rice varieties that meet farmers’ preferences. A survey of area under rice varieties at the farm level in three villages in Madhya Pradesh shows substantial diversity (Table 8). The diversity was due to large proportion of rainfed land, heavy soils, and variation of land forms within a village. Traditional variety Safri 17 (late duration) is preferred by farmers due to stable yield, insect pest and disease resistance, drought tolerance, and weed competitiveness. However, its yield is perceived to be lower than Swarna and Kranti, and it is susceptible to lodging. Swarna is a high-yielding, late-maturing semidwarf variety. Farmers perceive it to be drought-tolerant and responsive to fertilizer. It has a dark green color, which allows weedy rices to be identified. It has good eating quality, keeps well when cooked, and has a high milling recovery. Mahamaya has medium duration, high yield poten-

Table 8. Area (ha) planted to modern and traditional rice varieties by farming households in three villages. Raipur, Madhya Pradesh, 1997. Tarpongi (n = 25) Varietya Upland Lowland Upland Lowland Upland Lowland Saguni (n = 50) Khairkut (n = 50) Duration (d)

Modern Swarna Mahamaya Kranti 262 Purnima IR36 Culture
Others Total modern Traditional Safri-BD Safri-17 Chepti Gurmatia Ranikajar Bhata Safri Anjan Safri Ganga Safri Nankershar Dubraj Chepti Total traditional) Total all varieties % modern % traditional
a

0.8 6.8 7.5 2.4

7.8 2.6 6.9 2.1 0.4 0.8

27.6 2.2 8.8

9.9 1.4 1.8 0.1

38.7 6.6 4.9 0.8

5.0 1.0

0.6 1.9 1.2 0.7 15.1 0.4 51.4

Late (150) Medium (130) Medium (130) Medium (125) Late (145) Early (120) Medium (130)

17.5

20.6

40.5

6.6

2.9 1.2 10.8 1.8 4.4 0.5 0.3 0.2

28.4 10.7 7.0 1.4 7.8 0.1

7.7 12.3 3.2 6.3

4.1 3.7 3.8 1.9 0.4

40.6 0.4 0.6 5.7 2.1

5.2 5.0 0.4 1.6

Late (150) Late (155) Medium (130) Medium (130) Medium (130) Late (145) Late (145 ) Late (135) Medium (130)

1.6 22.1 39.6 44.19 55.81 57.0 77.6 26.55 73.45 29.5 70.02 57.87 42.13 4.7 18.6 33.7 44.81 55.19 49.4 100.86 50.92 49.08 12.2 18.8 35.11 64.89

Modern: semidwarf high-yielding varieties. Traditional: tall-statured, improved or not improved.

42

IRRI program report for 2000

Table 9. Comparison of rankings attributed by farmers and breeders at different growth stages in trials in Raipur villages, eastern India, 1997-99. Agreement among farmers Wb Trial location Year Stagea Varieties (no.) 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 20 20 20 20 20 20 Farmers (no.) 8 8 5 4 5 7 7 6 5 5 8 6 8 6 5 4 4 4 6 4 7 7 6 5 7 7 7 6 5 5 5 5 5 5 Breeders (no.) 1 1 – 2 – 2 – 2 – 2 2 2 2 2 1 1 1 1 1 1 3 3 3 3 3 3 3 3 3 3 3 3 3 3 0.34** 0.51** 0.51** 0.55** 0.50** 0.34** 0.30** 0.44** 0.79** 0.54** 0.32** 0.26 0.31** 0.67** 0.55** 0.30*** 0.56** 0.59** 0.38** 0.44* 0.49** 0.65** 0.65** 0.62** 0.53** 0.34** 0.50** 0.66** 0.98** 0.98** 0.96** 0.98** 0.94** 0.90** – – – 0.47 – 0.53 – 0.30 – 0.56 0.77 0.60 0.54 0.70 – – – – – – 0.91** 0.89** 0.94** 0.84** 0.81** 0.76** 0.93** 0.91** 0.94** 0.98** 0.97** 0.95** 0.99** 0.97** –0.20 0.11 – 0.13 – –0.03 – -0.18 – –0.06 0.16 0.50* –0.04 0.28 0.46 0.20 0.07 0.02 0.51* –0.01 0.33 0.62* 0.61* 0.46 0.15 0.11 0.66** 0.64** 0.90** 0.91** 0.89** 0.87** 0.92** 0.41** Agreement among breeders Wb Correlation between farmers' and breeders’ rankings (Rc)

Station Tarpongi

Saguni

Station

Tarpongi

Saguni Khairkhut Station Station Tarpongi 1 Tarpongi 2 Station Station Saguni 1 Saguni 2 Station Station Station Khairkhut Khairkhut Khairkhut
a

1997 1997 1997 1997 1997 1997 1997 1997 1997 1997 1998 1998 1998 1998 1998 1998 1998 1998 1998 1998 1998 1999 1999 1999 1999 1999 1999 1999 1999 1999 1999 1999 1999 1999 1999

F M F M F M F M F M F M F M F M Crop failure F M F M M M M M M M M M V F M V F M

F = flowering, M = maturity, V = vegetative. bW = Kendall’s coefficient of concordance. cR = Spearman’s coefficient of correlation.

tial, and some disease resistance. It also has the dark green color plus good straw and grain qualities. Its bold, heavy grains remain soft after cooking and poor consumers prefer it because even a small quantity makes them feel full for a long time. Two farmers in each village volunteered to grow a set of diverse materials using their labor and level of management. They experimented with two sets of medium-duration rice genotypes in Tarpongi village and one set each of late-duration varieties in Saguni and Khairkut villages, which have heavytextured soils. The set of genotypes included pre-

released F7-F8 and a local check. The same sets (16 genotypes) were tested on an experiment station. During different stages of crop growth (vegetative, flowering, and maturity), farmers and plant breeders ranked the varieties on the station and in farmers’ fields. The assessment of these varieties by breeders and farmers is shown in Table 9. Correlation between breeders’ and farmers’ evaluation at all sites and in all the years was consistently low. However, there was high agreement in varietal ranking among farmers and among breeders. This may indicate that farmers and breed-

Rainfed lowland rice ecosystem

43

ers consider different criteria. Farmers’ ranking is not correlated with yield, indicating that farmers are considering other criteria in their rankings. The four late-duration lines preferred by breeders in the 1999 trials were BKP232, R650-1817, R304-34, and R738-1-64-2-2. These are all modern varieties and also gave the highest yields. Farmers preferred Swarna, Safri 17, R738-1-64-2-2, Mahsuri, and R650-1817. These were not always highest yielding varieties and Safri 17 is a traditional variety. At Tarpongi, the top-ranking medium-duration varieties for breeders were R574-11, IR42342, Chepti Gurmatia, BG380-2, R703-1-52-1, and OR1158-261. All of those are also the top-yielding varieties. All are modern varieties except for Chepti Gurmatia. For farmers, the top-ranking varieties included BG380-2, OR1158-261, R714-2-9-3-3, IR63429, and R574-11. These are all modern varieties, but not always top-yielding. Farmers and breeders agreed only on R574-11, BG380-2, and OR1158-261. A weighted participatory ranking method was used in assessing the trade-off between traits preferred by male and female farmers. The most important traits that both men and women value in rice varietal selection are grain yield, eating quality (taste), market price, duration or maturity, drought tolerance, and resistance to insect pests and diseases. Women placed higher weights on multiple uses of straw across all land types and size of landholding. This may be because women are responsible for caring for livestock and gathering fuel, and rice straw is important in both activities. Men gave more importance to grain size and shape for varieties grown on the uplands. Men having small farms considered adaptation of varieties to specific soil conditions to be extremely important (second to yield), but were the only group to rank that factor highly. The challenge facing the plant breeders is to develop new cultivars better than Swarna and Mahamaya, which meet the requirements that farmers have for their rice environments. Giving farmers an opportunity to test the performance of different rice genotypes on their own fields and to evaluate their cooking and eating qualities can lead to development and fast dissemination of varieties appropriate to farmers’ needs.

Validation and delivery of new technology for increasing productivity of flood-prone ricelands of South and Southeast Asia
The main project objective is to evaluate and disseminate new technologies for sustainable increase in rice yields and rice land productivity in the floodprone areas. There are two major areas of emphasis: q farmer-participatory testing of adaptation of new rice production and resource management technologies including improved cultivars of rice in flood-prone ecologies, and q socioeconomic analysis to assess the viability and social acceptability of the alternative technologies and thus support dissemination of the most appropriate ones. Bangladesh, India, Vietnam, Sri Lanka, and Thailand participate. Activities are identified for different subecosystems (boro, deepwater, tidal nonsaline, and tidal saline) of the flood-prone rice lands. Developments in boro rice farming V.P. Singh and M. Dhanapala The boro rice crop in South Asia is essentially an irrigated DS crop that takes advantage of abundant sunlight and residual soil moisture and is practically free from climatic adversities, except in some areas of Bangladesh where early floods coincide with crop maturity. Boro is known as spring-summer rice in Southeast Asia. The cultivation of boro rice with traditional varieties used to be limited to the river basins and deltas because of nonavailability of water during the DS. With the availability of high-yielding, DS rice varieties, and with rapid expansion of irrigation coverage, boro rice farmers started growing modern rices in the DS and leaving the deepwater land fallow in the WS. Boro rice is now spread across Bangladesh and is grown in Assam, West Bengal, Orissa, and Bihar states in India. Major concerns for researchers are development of shorter duration and cold-tolerant boro varieties to escape early floods and increase cropping intensity in the system, and improvement of crop management for increased efficiency of crop inputs.

44

IRRI program report for 2000

IDENTIFICATION OF SUITABLE BORO VARIETIES

Advanced boro rice lines found superior in varietal screening were evaluated for single boro cropping pattern in seven farmers’ fields at Kuliarchar Thana and Karimgonj Thana, Bangladesh, with the objective of identifying short-duration, cold-tolerant, and high-yielding varieties. BR4828-54-4-1-4-9 yielded highest (5.9 t ha–1) and matured in 162 d. A recommended rice variety, BRRI dhan 29 (5.6 t ha–1), was the next best yielder, with maturity at 168 d. Farmers in Kuliarchar Thana preferred BR4828-54-4-1-4-9 to the recommended variety (BRRI dhan 29). In low-lying areas that flood prior to boro harvest, BR5877-21-2-3, which matures in 145 d was preferred by the farmers in despite lower grain yield (5.2 t ha–1). The advantage was its growth duration, which helps in escaping early flooding. It would also fit a double-cropped boro-deepwater aman system at medium flooding depth. Six rice lines (PSRM2-1-4B-15, RAU1344-3-2, IR59471-28-20-2-1, Panjasali, TRB7, and Banglami) were identified in Assam, India, as superior to the local checks. These promising lines were subjected to farmer participatory validation of their performance in Assam and Bihar. In Bihar, RAU1345-3-2 and RAU1344-3-2 performed well. Both had higher cold tolerance and shorter duration than the local check Gattu. RAU1345-3-2 was preferred by most farmers. It was recommended and released as variety Richharia and genotype RAU1344-3-2 was released as Dhan Laxmi for boro cultivation. Panjasali (192 d maturity) recorded the highest grain yield (9.37 t ha–1) in Assam. IR50 had a yield of 7.85 t ha–1 with maturity at 183 d. Both were superior to Mahsuri, the farmers’ check variety, which recorded a yield of 6.6 t ha–1 in 209 d.
CROP ESTABLISHMENT

A comparison of wet-direct seeding with conventional transplanting was done in farmers’ fields in Basail, Bangladesh, using the commonly grown varieties BRRI dhan 28, BRRI dhan 29, and BRRI dhan 36. The wet-direct seeded rice had a 10–14 d earliness in maturity and a yield advantage of 0.7– 1.1 t ha–1 over the transplanted system, mainly because of timely crop establishment.
NURSERY MANAGEMENT

The nonavailability of early maturing, high-yielding boro rice varieties with cold tolerance at the seedling stage is a major constraint to boro rice cultivation because seedlings have to be raised during the cold winter season to be ready for timely crop establishment. Nursery management techniques were compared for three varieties of rice (Pusa 221, Jaya, and IR56383-7-1-1-1): q covering the seedlings with polythene during the night to conserve the heat through restricted air circulation, q early -morning removal of dew drops from the seedling leaves to prevent leaf scotching caused by evaporating dew drops, and q dusting cowdung ash over seedling canopy to insulate against heat loss from the seedlings. All the three management techniques significantly contributed to the survival of seedlings, including the susceptible genotype Pusa 2-21. Covering seedlings with a polythene sheet provided the best results.
CROP MANAGEMENT

Timely crop establishment is of essence in boro rice farming because of temperature and growth duration, and the risk of flooding at maturity stages. The boro crop is traditionally a transplanted crop, wherein the requirements for a nursery delays transplanting.

Boro rice requires several irrigations during the growing season. Farmers in Assam, India, for example, provide as many as 32 irrigations per crop, each with about 7 cm water depth, mostly from shallow tubewells. A field demonstration of applying 7 cm water, 3d after the disappearance of water from previous irrigation (i.e., about 7 cm irrigation every after 8 d) in 10 farmers’ fields at Katimari village, Shillongani, Nagaon, Assam, achieved a water economy of more than 50%, without sacrificing any crop yield, when compared with farmers’ practice using same rice variety, crop management, and crop

Rainfed lowland rice ecosystem

45

growing periods. Average yields were 7.7 t ha–1, exactly the same as obtained with the farmers’ practice of applying 15 cm water every 8 d.

Progress of unreported projects
Rainfed Lowland Rice Research Consortium
q q

q

q

At CRRI-Cuttack in India, the farm mechanization group and IRRI collaborators worked to identify opportunities and priorities for adaptive research on agricultural mechanization. Initiated a farmer participatory experiment on validation and evaluation of drought-tolerant breeding lines. At NDUAT-Faizabad in India, five genotypes from the participatory varietal selection (PVS) program from 1997 to 1999 were tested in shallow, drought-prone rainfed lowland farmers’ fields in Mungeshpur and Sariyawan, Faizabad District. In Mungeshpur, PVS7 (NDRSB9830102) and PVS10 (NDRSB9730020) were the preferred varieties grown by nine farmers. Yields of PVS7 ranged from 2.5 to 3.8 t ha-1. Farmers in Sariyawan grew PVS1 (GayaPrasad Maurya) and PVS7. Farmers preferred PVS7 because of its good yield, suitability to land type, medium bold and cylindrical grains, good milling recovery, good eating quality, good quantity and quality of rice straw for animals, and ease in threshing due to their long stalks. Because of its short maturity (less than 120 days), rabi crops can be grown after PVS7, whose seeds are now spreading in nearby villages. At MMSU-Batac in the Philippines, recent economic analyses have shown that positive trends in total factor productivity in 1992-95 had turned negative in the subsequent period from 1996 to 1997. At an N rate of 120 kg ha1 , as recommended to improve input-use efficiency and sustainability, crop residue reincorporation further increased rice yields by 0.4 t ha-1. Responses of the five dry-season rotation crops to this new fertilizer recommendation varied, but sweet pepper crops continued to accumulate nitrate in the groundwater. This highlights the need for green manure or catch crops to reduce

q

q

leaching of nitrate. To improve farmer awareness, at least 8,000 rice farmers in the region were given updated information on the potential of indigo as a green crop to enhance productivity in these intensifying rice-based cropping systems. AT RRIT-Ubon Ratchathani in Thailand, 12 promising lines were selected from observation nurseries under drought-prone rainfed lowlands and evaluated on-farm at five locations in the northeast and one in the north. The promising lines IR68796-27-3-B-5-2-B, IR69515-27-KKN-1-UBN-1-1-1-B, and IR57549-PMI-13-1-2-1, considered well suited to drought-prone poor soils and resistant to leaf and neck blast and iron toxicity conditions, will be nominated for release. Ten other promising lines, IR70182-18-PMI-7-2B, IR70215-70-CPA-3-4-1-B, IR71506-27-21-B, IR69515-27-KKN-1-UBN-1-1-1-B, IR68796-27-3-B-5-2-B, IR70172-1-SRN-4-1B-1-B, IR68835-133-3-B-B-4-2-B, IR6883544-5-B-B-9-3-B, IR68835-130-B-B-2-B-B1B, and IR68835-130-B-B-2-B-B2-B, had high yield, tolerance for some drought at early and flowering stage and resistance to blast. These lines will be evaluated on-farm to test adaptability at farm level. Of 1,668 breeding lines from Thai-IRRI shuttle research and 1,201 from the Thai breeding program, 70 and 36%, respectively, showed resistance to leaf blast; of these, more than 50% were resistant to neck blast. AT IGAU-Raipur in India, a regional analysis of rainfed ecosystems is being conducted at the micro scale, leading to a climatological assessment of drought incidence in Madhya Pradesh. The results are being mapped as an agroclimatic atlas for distribution to farmers. Nutrient management studies for improving the residual and applied P and nitrogen-use efficiency in rice-based systems are leading to an improved management package for the entire cropping system, which is being documented as a resource book for scientists, extensionists, and farmers. At CRIFC-Jakenan in Indonesia, recent findings in tillage, crop establishment, and weed management were published in the

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IRRI program report for 2000

q

international workshop on direct seeding. The results demonstrated the clear associations of weed species with toposequence position and soil fertility levels. Further experiments were set up at selected sites in central Java to quantify nutrient and water variability and weed community dynamics across toposequences in rainfed lowland rice. At BRRI-Rajshahi in Bangladesh, a long-term study of productivity and sustainability in rainfed rice-rabi cropping systems has begun. During 2000, an additional component on weed succession in the different rotations was added to the long-term experiment. ON-farm yield gap studies have indicated that any change from transplanting of rice to direct seeding increased the requirement for handweeding from one to three times. Although farmers are interested in direct seeding to bring the rice harvest forward to allow timely planting and reduced drought risk in the rabi crop, they are unlikely to change from transplanting unless the weeding issue is resolved. Accordingly, the third treatment in the long-term experiment now includes the use of Ronstar as a preemergent herbicide in the direct-seeded rice crop.

q

Promoted need-based nitrogen management in boro rice, including the field testing of the leaf color chart in Bangladesh.

Program outlook
Research activities in the rainfed lowlands and upland rice ecosystems were combined into one program, Improving Productivity and Livelihood for Fragile Environments, in the new medium-term plan (MTP), implemented in 2001. The new program will focus on developing stress-tolerant, high-yielding varieties and efficient crop management practices that will reduce risk in rainfed and upland rice cultivation. Research partnerships with NARES to facilitate collaborative research aimed at understanding and developing technology and expertise to improve the productivity of rainfed lowland and upland systems will continue. Problems and issues will be addressed in three projects: q Genetic improvement for improving productivity and human nutrition in fragile environments, q Natural resource management for rainfed and upland systems, and q Rice research consortia for fragile environments. Work on improved crop and resource management for the deeply flooded and coastal areas will continue to focus on understanding the nature and implications of emerging changes in these areas and strategic research needed for improved productivity and sustainability of these fragile systems. Genetic enhancement of rice for unfavorable environments is seen as an activity with high potential for gains in food security, human nutrition, poverty reduction, and environmental protection. Under the new MTP, work in this area, involving many disciplines and utilizing new and traditional methodologies will be in a project, Genetic Enhancement for Improving Productivity and Human Health in Fragile Environments.

Facilitating technology transfer among NARES for the flood-prone rice ecosystem
q

q

q

q

Completed benchmark socioeconomic survey in flood-prone environments and its data analysis in Bangladesh. Developed a new plant type of deepwater rice in which elongation is triggered at a certain water depth and field-tested 52 lines in Bangladesh in the 2000 wet season. Conducted participatory testing and evaluation of new tidal saline and tidal nonsaline rice types for two seasons in Vietnam, Sri Lanka, Bangladesh, and India. Demonstrated the viability of wet seeding and the “dapog method” of raising seedlings and nursery management options for lowtemperature survival of boro rice in Bangladesh and India.

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47

Research programs Upland rice ecosystem

IMPROVED PRODUCTIVITY AND SUSTAINABILITY OF FARMING SYSTEMS IN UPLAND RICE AREAS 50 Population pressure, market access, and food security in the uplands of northern Vietnam 50 Beyond traditional upland rice: a high-yielding rice production system in aerobic soil 52 Planting density and tiller production 53 Plant height and biomass density 53 Grain yield and harvest index 54 Nitrogen supply, crop N accumulation, and partitioning 54 Yield performance over time 54 Causes of loss in crop performance over time 55 Farmers’ practice of using salt for weed control in upland rice 56 Use of salt to control Ageratum conyzoides L. 56 Effects on soil conditions 57 Effects on the upland rice crop 58 Improvement of N use efficiency with the use of controlled-release N fertilizer in upland rice in eastern India 59 Factors affecting grain yield 59 Nitrogen recovery and root growth 61 Strategies for improving productivity 61 UPLAND RICE RESEARCH CONSORTIUM 62 Workshops 62 Long-term Phosphorus Experiment Workshop 62 Aerobic Rice Workshop 62 Commercialization, land use changes, and food security in the uplands of northern Vietnam 62 Weed Management Workshop 63 PROGRESS OF UNREPORTED PROJECT Genetic improvement of upland rice 63 63

Upland rice ecosystem

Upland rice covers about 20 million ha across Asia, Africa, and Latin America. Because it grows in environments where drought and problem soils are prevalent, yields average 1 t ha–1. The Upland Rice Ecosystem Program has three projects: q Genetic improvement of upland rice q Improved productivity and sustainability of farming systems in upland rice areas q The Upland Rice Research Consortium (URRC) The report for this year focuses on improved productivity and sustainability of farming systems.

Improved productivity and sustainability of farming systems in upland rice areas
Population pressure, market access, and food security in the uplands of northern Vietnam S. Pandey, N.T. Khiem, N.H. Hong, and H. Waibel A study in the northern uplands of Vietnam examined the effect of population pressure and market access on cropping patterns, cropping intensity, extent of commercialization of production systems, land and labor productivity, household food supply, and overall level of poverty. The analysis was based on a cross-sectional survey of 980 farm households from 33 communes of six provinces during crop year 1997-98. The main characteristics of the households are summarized in Table 1. The data show that upland rice accounts for a large share of rice supply in areas with poorer access to markets. The hypotheses tested using regression analysis were q Cropping intensity is positively related to population density and is negatively related to market access. q Land and labor productivity is higher in areas with better access to markets. q Cropping intensity in uplands is lower in areas with a relatively higher proportion of lowland area. q Land and labor productivity in upland agriculture is positively affected by better access to markets. q The extent of food shortage depends on land and labor endowments as well as access to markets.

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IRRI program report for 2000

Table 1. Household characteristics of low and high market access among 980 households in 33 communes of northern Vietnam, 1997-98 cropping season. Item Sampled households (no.) Av household size Annual production per household (kg) Lowland rice Upland rice Maize Av area per household (ha) Lowland Upland Upland rice Upland maize Home garden Annual total income (US$) Cash income Sales of crop products Sales of livestock Sales of forest products Sales of home garden products Nonfarm income Noncash income Share of cash income (%) Per capita income Lowland rice area/lowland area Upland rice output/total rice output Fallow cycle of upland fields (years)
a

Low market accessa 605 7.7 769 606 531 0.235 1.030 0.436 0.327 0.031 559 213 34.6 85.6 11.2 6.8 75.0 344 34.7 78 1.09 0.44 5.0 (0.14) (39) (23) (25) (0.02) (0.04) (0.02) (0.01) (0.01) (89) (12) (2.5) (4.5) (2.7) (1.4) (10.8) (11) (2.8) 6.9 1134 320 511

High market accessa 375 (0.15) (49) (21) (38) (0.01) (0.02) (0.01) (0.02) (0.01) (55) (20) (3.6 (13) (0.05) (8.5) (6.9) (13) (3.5)

0.291 0.590 0.239 0.234 0.058 686 310 37.8 134.7 4.4 52.6 81.2 374 40.0 103 1.40 0.22 4.5

(0.10)

(0.08)

Numbers in parentheses are standard errors.

Regression analysis indicated that cropping intensity was higher in communes with a higher population density. Intensification occurred through both a reduction in the fallow period and an increase in crops per cropping cycle. Land and labor productivity and cash income were higher in areas with good access to markets than in areas with poor access. Inspite of these positive effects, the agricultural production system was found to be predominantly subsistence-oriented, with farmers striving to achieve food self-sufficiency even in areas where the importance of cash crops was high. Cropping intensity in the upland area was negatively related with the size of the lowland holding, indicating that an improvement in lowland productivity can help reduce the intensification pressure in the upland. Farmers with good access to markets and with larger farms had a lower incidence of food shortage than those with limited access to markets and with smaller farms. A simulation model was developed to project the likely effect of continued increase in population pressure on food production, labor absorption in

agriculture, calorie consumption per capita, and extent of poverty. The effect of rising population pressure on food production was simulated, assuming that the current agricultural productivity of different land-labor quartiles applies to the households as they move across the quartile groups. The static projection (Table 2) indicated that while the labor force will increase by 65% in 20 years, labor use in crop production will increase by only 9%, thus showing the need to expand labor absorption in the noncrop sector. Crop production with existing technology will increase by only 5% of its current value, leading to a dramatic decline in per capita food supply. The growth in rice yield (both upland and lowland) of at least 2% y–1 is needed to maintain the current per capita calorie intake. An improvement in upland rice yield was found to be an important strategy in reducing the poverty of the low-income quartile group that depends mostly on upland rice (Table 3). Given the size of the population growth, the overall reduction in poverty will also require an expansion of employment

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Table 2. Simulation of growth in labor force, production of major food crops, and per capita calorie intake for 2009 and 2019 based on data from 980 households in 33 communes of northern Vietnam, 1997-98 cropping season. Item Baseline 1999 2009a (Index: 1999 = 100) Population Labor force Consumer unit equivalent Labor input in crop production Food crop production Scenario 1b Scenario 2c Scenario 3d Scenario 4e Per capita caloric intake Scenario 1b Scenario 2c Scenario 3d Scenario 4e 100 100 100 100 100 100 100 100 100 100 100 100 125 135 130 104 103 110 118 125 80 90 90 99 161 176 165 109 105 121 141 157 65 82 82 98 2019a

a Projection based on agricultural population growth of 2.38% y–1. bAssumes yields of lowland and upland food crops remain unchanged. cAssumes yield of lowland rice increases at 2% y–1 but yields of upland crops remain unchanged. dAssumes yields of upland food crops increase at 2% y–1 but that of lowland rice remains unchanged. eAssumes yields of lowland rice and upland food crops increase at 2% y–1.

Table 3. Simulated effect of various interventions on poverty (percentage of households below the poverty line) based on data from 980 households in 33 communes of northern Vietnam, 1997-98 cropping season. Income group (quartile) Item Lowest Benchmark value (1999) 50% increase in upland rice yield 50% increase in lowland rice yield 100% increase in upland rice yield 100% increase in lowland rice yield 50% increase in noncrop income 50% increase in noncrop income and upland and lowland rice production 88 78 81 75 75 85 67 Second 71 62 62 50 56 65 38 Third 53 42 35 27 25 45 19 Highest 23 16 8 13 4 13 4 All 59 50 46 40 40 52 32

in the noncrop and nonfarm sectors. The main findings of our study: q Upland rice is a critical component of the household food supply, especially in remote areas and where there is poor access to markets. q Improvements in yield of upland rice can have a positive impact in reducing poverty, especially for those of the lowest income groups. q Further expansion of market access and development of more effective marketing institutions are needed to expand incomegenerating activities in uplands.

q

A regionally differentiated strategy for agricultural diversification that recognizes the environmental diversity in these upland systems is needed to promote an overall income growth.

Beyond traditional upland rice: a highyielding rice production system in aerobic soil T. George, R. Magbanua, B. Tubaña, and J. Quiton Upland rice is generally perceived in Asia to be unsuitable for production environments geared for high yields. However, should irrigation water defi-

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IRRI program report for 2000

cits develop, some of the double- and triple-crop flooded-rice systems of today are likely to evolve into rotational systems with high-value upland crops. We investigated management options for highyield rice production in aerobic soils with the objectives of q analyzing performance of rice genotypes in aerobic soil in the absence of nutrient and water stresses, q examining biomass and nutrient accumulation characteristics that confer high yields for rice in aerobic soil, and q identifying research issues to be addressed for sustaining high yield of rice in aerobic soil. Experiments started in 1998 consisted of treatments of plant population; lowland or upland cultivars from IRRI, the West Africa Rice DevelopTable 4. Grain yield and total biomass of upland and lowland rice varieties grown at different populations in aerobic soil with ample supply of nutrients and water, Siniloan, Laguna, Philippines, 1998 DS. Plant densitya (1000 seedlings ha–1) Cultivar 1.2 2.4 Grain yield (t ha–1) Lubang Red IR55423-01 IR72 Magat (IR64616H) Mean 2.3 5.1 4.9 7.6 5.0 2.4 5.4 4.8 8.2 5.2 1.5 5.5 4.9 7.8 4.9 4.8 1.2 2.4 4.8

ment Association, and the Brazilian Institute for Agricultural Research; soil aeration status; and plot history. This is a preliminary report of the major findings.

PLANTING DENSITY AND TILLER PRODUCTION

Dry-season grain yield and biomass were about the same from plant densities ranging from 1,200 to 4,800 seeds ha–1 (Table 4). The lack of any effect of planting density on yield seemed to be in part due to a compensating effect on biomass accumulation from greater tiller production. A reduction in planting density from 4,800 to 1,200 seeds ha–1 was associated with only a 21% average reduction in tiller number at maturity because individual plants produced more tillers at the lower planting density. Further, the tiller production observed for two lowland varieties (average of 857 tillers m–2) in aerobic soil was substantially higher than the about 500 tillers m–2 usually reported observed for the same cultivars as a flooded, transplanted crop. Aerobic soil culture seems to favor high tillering in rice.
PLANT HEIGHT AND BIOMASS DENSITY

Total biomassb (t ha–1) 11.3 15.7 15.2 16.0 14.5 11.6 15.5 15.8 17.0 14.9 9.6 15.0 15.4 15.9 14.0

a Established an av of 3 seedlings hill–1 by dibbling seeds at 2.5, 5, or 10 cm spacing within a row and 25 cm between rows and thinning as necessary at 2 wk after seeding. bOven-dried basis.

Plant height of lowland cultivars both IR72 and Magat were substantially lower than both Lubang Red, a Philippine traditional upland rice cultivar, and IR55423-01, an elite upland rice being released as a new cultivar (Table 5). Plant height of lowland cultivars was substantially lower than the upland cultivars and was also lower than plant height of the same cultivars when grown in flooded soil. For ex-

Table 5. Tiller number, plant height, biomass height, and biomass density of upland and lowland rice cultivars grown at different populations in aerobic soil with ample supply of nutrients and water, Siniloan, Laguna, Philippines, 1998 DS. Tillers (no. m–2) at planting densitya (1,000 seedlings ha–1) 1.2 Lubang Red IR55423-01 IR72 Magat (IR64616H)
a

Cultivar

Plant height at maturity (m) 4.8 368 519 873 1039 1.28 1.03 0.70 0.67

Biomass heightb (m)

Biomass densityc (kg m–3)

2.4 350 326 767 901

329 331 716 845

0.12 0.07 0.05 0.04

0.8 1.5 2.2 2.4

Av 3 seedlings hill–1 by dibbling 3–4 seeds at 2.5, 5, or 10 cm spacing within a row and 25 cm between rows and thinning 2 wk after seeding. bHeight of aboveground biomass per unit weight and area. cWeight of biomass per unit bulk volume of aerial space occupied by the plant.

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ample, the plant height of Magat at maturity in flooded soil culture averages 91 cm in DS and 105 cm in WS (IRRI IRIS database) compared with 67 cm observed in our experiment. This reduction in plant height when grown in aerobic soil was also observed across several upland cultivars and one lowland cultivar in 2000 experiments. Height reduction ranged from 16 to 37% when measured at 13 wk after seeding. The reduced height of IR72 and Magat combined with their profuse tillering resulted in substantially lower biomass height and substantially higher biomass density than for the upland cultivars (Table 4). The biomass height of Magat was just 0.04 m t–1 ha–1 compared with 0.07 for IR55423-01 and for Lubang Red. On the other hand, the biomass density of 2.4 kg m–3 of Magat was 2.8 times higher than Lubang Red and 1.6 times higher than IR55423-01. The low biomass height and high biomass density of Magat and IR72 are likely to help the crop resist lodging better than taller cultivars such as IR55423-01 and Lubang Red.
GRAIN YIELD AND HARVEST INDEX

Table 6. Total and grain N uptake by upland and lowland rice cultivars grown at different populations in aerobic soil with ample supply of nutrients and water, Siniloan, Laguna, Philippines, 1998 DS. Cultivara Lubang Red IR55423-01 IR72 Magat (IR64616H) Total N (kg ha–1) 155 186 179 196 Grain N (kg ha–1) 30 69 56 99

a Av of 3 seedlings hill–1 2.5, 5, or 10 cm spacing within a row and 25 cm between rows and thinning 2 wk after seeding.

NITROGEN SUPPLY, CROP N ACCUMULATION, AND PARTITIONING

The cultivars grown in 1998 DS varied significantly in grain yield. Magat, a lowland hybrid rice, yielded an average of 7.8 t ha–1. Lubang Red, an upland traditional cultivar, yielded only 2.1 t ha–1 (Table 4). All three improved rice cultivars produced similar total biomass, thus the highest yield of Magat was from its highest harvest index (ratio of grain to total biomass). The low yield of Lubang Red was the result of its somewhat lower biomass and the lowest harvest index. Thus, while all cultivars, particularly the improved ones, were able to accumulate substantial quantities of biomass, only Magat had a significant portion of it in grains. The 7.8 t ha–1 yield of Magat in aerobic soil is comparable with its reported yield of 7.2 t ha–1 in flooded soil during DS (IRRI IRIS database). IR72, despite height and weight characteristics similar to Magat, did not yield as much as Magat due to lower harvest index in the aerobic soil, a possible indication of the importance of cultivar adaptation to aerobic soil culture. Magat may provide the basis to identify factors that led to its higher harvest index in aerobic soil.

The crop N accumulation and partitioning of N to grains followed the same pattern as biomass accumulation and grain production (Table 6). The three improved cultivars accumulated similar amounts of N, averaging about 187 kg ha–1 compared with 155 kg ha–1 by Lubang Red. All cultivars differed in the amount of grain N, with Magat partitioning 51% of its total N into grain compared with a low 19% in Lubang Red. The crop in 1998 DS was supplied with a total of 100 kg N ha–1 in doses of 10–20 kg ha–1 applied from 3 wk to 11 wk after seeding. At a 50% assumed recovery of fertilizer N, the fertilizer N component of the crop N would be about 50 kg ha–1. Thus, the soil N contribution to the improved cultivars is estimated at 137 kg ha–1, a rather high amount. Even if a greater than 50% crop recovery of fertilizer N is assumed, the soil N contribution is still higher than what would be normally expected. The soil N uptake by a P-fertilized non-N2-fixing soybean crop in the same soil in a neighboring experiment averaged only 42 kg ha–1 across four DS. Thus, it appears that soil N extraction by all four rice cultivars in 1998 DS was extremely efficient in aerobic soil culture. Such high efficiency of soil and fertilizer N use is rarely achieved in flooded rice culture.
YIELD PERFORMANCE OVER TIME

Grain yield and biomass of several cultivars grown in aerobic soil in the same experiment from 1998 DS to 2000 WS are presented in Table 7. Rice was

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IRRI program report for 2000

Table 7. Grain yield and biomass of upland and lowland rice cultivars grown repeatedly in the same plots in aerobic soil with ample supply of nutrients and water, Siniloan, Laguna, Philippines, 1998 DS-2000 WS. 1998 Cultivar Dry season Wet season Dry season Wet season *a *a – – *a – – 1.5f 1.4f – – 1.3f – – Dry season xb x x x x x x x x x x x x x Wet season 4.0c 3.8c – – – – 2.4c 3.3 3.1 – – – – 2.4 1999 2000

Grain yield (t ha–1) IR55423-01 Magat (IR64616H) IR72 Lubang Red Mestizo (IR68284-H) Primavera UPLRi-5 Biomass at 10 wk (t ha–1) IR55423-01 Magat (IR64616H) IR72 Lubang Red Mestizo (IR68284-H) Primavera UPLRi-5
a

5.3 7.8 4.9 2.1 – – 6.9 6.6 6.1 7.9 – – –

3.6 –d – – – 1.8 – 5.8 – – – – 5.2 –

3.4 – – – 3.0 2.0 – 3.8e – – – 4.3f 3.8f –

Only biomass harvest. Grains unfilled and plants severely affected by disease complex including that of tentatively identified bacterial sheath brown rot caused by Pseudomonas fuscovaginae. bPlots grown to maize-cowpea intercrop. cGrain yield estimated from 70-day biomass using relationships between biomass and grain yield in normal seasons. Grain yield variably and severely damaged among cultivars and plots by flooding, crop submergence, and winds during the reproductive period. dPlots grew different rice cultivars. eTen-week biomass estimated from biomass data at 65 and 78 d by linear interpolation. f Ten-week biomass estimated from biomass data at 61 and 86 d by linear interpolation.

grown in aerobic soil in all seasons except the 2000 DS when a maize-cowpea intercrop was grown. The improved cultivar IR55423-01 was grown throughout but other cultivars were grown only in some seasons. Rice crop performance declined drastically with repeated cropping in aerobic culture, but the crop appeared to have recovered some in 2000 WS following the 2000 DS maize-cowpea intercrop. The 10-wk biomass in 2000 WS averaged 3.2 t ha–1, the same as in 1999 WS for the two cultivars—a 130% increase in biomass. Estimated grain yield data for 2000 WS are presented but should be interpreted with caution because the plots and cultivars were variably damaged from flooding, strong winds, and crop lodging during the reproductive period. Nonetheless, it appears that grain yield would have been higher than previous seasons if the weather was not crop damaging. While the maize-cowpea intercrop seemed to have helped reverse the decline in crop performance, the biomass production in the repeat crop plots in the 2000 WS averaged only half that observed for the same cultivars in the newly established fallow plots (Table 8). The differences between the crops in the repeat and fallow plots were also obvious in the field. Plants were greener and taller, hills were larger, and canopy was more closed

in the fallow plots. Crop growth in the new fallow plots was similar to the first crop in 1998 DS in the repeat crop plots.
CAUSES OF LOSS IN CROP PERFORMANCE OVER TIME

The recovery of crop biomass accumulation in 2000 WS, as well as the substantially high biomass production in the fallow plots with no previous upland rice history, are strongly indicative of a negative influence of continuous rice crops, or a preceding rice crop, on the performance of a subsequent rice

Table 8. Aboveground biomass at 13 wk after seeding of rice cultivars grown in plots repeatedly cropped to upland rice or following fallow. Siniloan, Laguna, Philippines, 2000 WS. Biomass (t ha–1) Cultivar Repeat plots IR55423-01 Magat UPLRi-5 Canastra WAB450-11-1-P31-1-HB WAB450-24-3-4-P48-3-1 WAB450-I-B-P-38-HB 4.6 4.1 3.6 2.6 1.5 1.8 1.9 Fallow plots 8.5 8.5 7.2 4.0 3.1 5.6 4.3

Upland rice ecosystem

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crop in aerobic soil. The maize-cowpea rotation in the repeat-crop plots of 1998 appears to have helped the rice crop partially recover from built-up biotic or abiotic stresses, which remain to be identified. The substantially higher biomass production observed in the fallow plots indicates that a one-season rotation of maize-cowpea intercrop was not sufficient to undo the growth stresses that built up during four preceding rice crops. Maize and cowpea are rated resistant to the upland rice root-knot nematode Meloidogyne graminicola. Previous studies (IRRI Program Report for 1993) indicated a strong association between the number of years of upland rice cropping or low upland rice yields and the buildup of M. graminicola or Pratylenchus spp. It is possible that the apparent reversal in biomass decline we observed was partly due to a break in nematode buildup with the nonhost maize and cowpea crops. However, soil and root nematode data collected 14 wk after seeding from the repeat plots and the fallow plots indicated no prevalence of M. graminicola or Pratylenchus spp. It is possible that nematode populations were affected by flash flooding and crop submergence that occurred 3 wk before sampling soil and roots for nematodes. This research shows that rice can be highly productive in upland aerobic soils if management is optimal for high-yielding genotypes. While our results demonstrated the potential for achieving high yield, they also raised new crop improvement and management issues to be addressed in order to sustain high yields in aerobic soil. Farmers' practice of using salt for weed control in upland rice K. Van Keer, G. Trébuil, and A. Thirathon Many upland rice farmers in northern Thailand are not able to control broadleaf weeds by customary practices such as fallowing, burning, hoeing, and hand weeding. Some farmers have turned to using unpurified common salt (NaCl) against Ageratum conyzoides L. and other Asteraceae species, which are major weeds of upland rice. The practice has also been reported in India and Ghana. Possible harmful effects of salt on soil and crops are unknown. Our preliminary investigation sought basic information on the use and effects of the practice.

USE OF SALT TO CONTROL AGERATUM CONYZOIDES L.

Field data were collected between 1993 and 1996 in the Lahu ethnic village of Mae Haeng, Fang District, Chiang Mai Province. Upland rice is grown on deep granite-derived Humic or Haplic Acrisols of medium fertility and slopes varying from 0 to 70%. Average annual rainfall is 1,500 mm (minimum 1,375 mm, maximum 2,292 mm during the 4-year survey period) with 90% of precipitations between May and October. Local upland rice cultivars are grown in swidden fields with no external inputs other than the occasional use of salt. Fallow periods ranged from 3 to more than 10 years, and crop successions from 1 to 3 years. On-station field experiments were established at Mae Sa Mai station, Mae Rim District, Chiang Mai Province, under similar environmental and pedologic conditions. Pot and laboratory experiments were done at the Department of Soils and Fertilizers, Maejo University, Chiang Mai. During the 4-year on-farm survey, salt spraying was observed in 15 of 65 upland rice fields (23%). The technical aspects of this practice are described in Table 9. Farmers use it mainly to control A. conyzoides L. and only in case of extreme weed infestation, lack of labor, or both. An herbicidal salt solution is applied once during the crop cycle, usually at the first (often delayed) weeding. Salt application is not repeated in the same field the following cropping season. When the level of weed control achieved was not satisfactory (due to rainfall just after spraying or to a large number of weed species not affected by salt), an additional manual weeding was done. Based on field observations and pot experiments, this technique seems to be effective to control A. conyzoides, one of the most common weeds occurring at high densities (sometimes more than 1,000 plants m–2). When subjected to an application of 150 kg NaCl ha–1 or more during dry climatic conditions, 45-dold Ageratum seedlings grown in pots displayed severe wilting 1 h after application and chlorosis symptoms appeared after 1 d. Wilting was irreversible after 3 d and plants did not recover after watering. However, weed control obtained in the field was only temporary. New weed seedlings emerged within a few weeks after salt application because of the apparent absence of an inhibitory effect of salt

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Table 9. Description of the technique using salt (NaCl) solution as an herbicide in upland rice (Mae Haeng village, 1993-96 on-farm survey). Formulation and dose Carrier liquid Cation content of the salt granulesa Concentration of the salt solutionb Application rate of the saltc Application rate of the solutiond Surfactant Application method and conditions Application method Application frequency and period Upland rice development stage Optimum climatic conditions Level of weed infestation Knapsack sprayer; solution sprayed directly on the weeds, avoiding contact with the rice Single application between 30 and 60 DAS 4–9 leaves, 20–80 cm plant height Sunny day, preceded by several dry days Density: from 30 to more than 1,000 plants m–2. Height 5–30 cm; soil cover 15–90%. Dry weight 10–150 g m–2. Water Na: 25–35%, K <0.2%, Mg <0.5%, Ca <0.4 % 36–120 g Na L–1 or 100–300 g NaCl L–1 35–450 kg Na ha–1 (av = 184) or 90–1,150 kg NaCl ha–1 (av = 467) 1500–3000 L ha–1 Small amount of washing powder

a Based on samples of salt granules taken from four farms. bBased on samples of salt solution taken from four farms. cCalculated as the difference in total soil Na-content (in the upper 5-cm soil layer) between sprayed and nonsprayed zones in 18 fields. dEstimates obtained from four farms where samples of both herbicidal solutions and soils were available.

on weed seed germination and the rapid removal of the salt from the topsoil. The type and rapidity of appearance of observed stress symptoms, the absence of differences when using different application rates, the improved efficiency under dry conditions, and the rapid reemergence of weed seedlings after the treatment suggest that the herbicidal effect of NaCl on A. conyzoides is primarily an osmotic effect rather than a specific ion effect. Pot experiments showed that solutions of salts other than NaCl (i.e., mineral fertilizers such as potassium chloride, ammonium sulfate, and urea) generated similar herbicidal effects on A. conyzoides when applied at osmotic concentrations equivalent to that of a 200 g L–1 NaCl solution (–165 atm). Herbicidal use of urea was actually observed at our study site and elsewhere in northern Thailand. In a second pot experiment, the lowest tested osmotic concentration of a salt solution causing irreversible dehydration of Ageratum seedlings was –50 atm (equivalent to 60 g NaCl L–1). This is in agreement with the literature stating that the osmotic potential of leaf cells of most (nonhalophytic) plants is in the range of –5 to –40 atm. Besides the target weed A. conyzoides, several other common Asteraceae weeds in swidden upland fields [such as Crassocephalum crepidioides Benth.

S. Moore; Spilanthes paniculata Wall. Ex. DC.; Bidens pilosa L. var. minor (Bl.) Sherff] were controlled by solutions of NaCl or other mineral salts. Other broadleaf weeds and grasses and sedges were less affected or not affected by salt spraying.
EFFECTS ON SOIL CONDITIONS

Regardless of the salt application rate (from 190 to 572 kg NaCl ha–1) or slope angle of the field (0–65 %), the electric conductivity (EC 1:5) of the topsoil layer (0–5 cm) increased shortly after salt application but returned to its initial level at the end of the cropping cycle (Fig. 1). That indicates that the salt is easily removed from the topsoil through leaching, runoff, and erosion. Although peak levels of ECe (saturated paste electric conductivity, estimated as ECe = EC 1:5 × 6.4) were high shortly after spraying (1,000–3,000 µS cm–1), they remained below the critical level for rice cited in the literature (3,500 µS cm –1 ). Similar observations were made for absolute salt concentrations in the topsoil. Additional studies on the fate of the salt after application were done with controlled field experiments (Fig. 2) and artificial leaching trials in a laboratory (results not shown). Those studies confirmed that NaCl is rapidly and entirely removed from the topsoil when the farmers’ application technique is used.

Upland rice ecosystem

57

EC1:5 (µS cm–1) 500 400 300 200 100 0 190 236 264 428 503 544 NaCl sprayed in fields (kg NaCl ha–1) 572
Before spraying 1–7 days after spraying End of rainy season

1. Changes in electric conductivity of the topsoil (0–5 cm) of upland rice fields before and after the application of varying amounts of herbicidal salt solutions. Mae Haeng village, Thailand, 1994 and 1995 WS.

EC1:5 (µS cm–1) 200 150 100
)
Topsoil Sediment Runoff

50 0 200 150 100 50 0 0

land in northern Thailand are dominated by kaolinitic clays and sesquioxides, and can tolerate high Na levels before soil structure deteriorates. Furthermore the salt is subject to intense leaching as it is applied early in the rainy season. Adding to this, farmers spray only in exceptional cases, never do so twice in the same field, and the treated fields are scattered and in fallow rotation. It is unlikely that this practice will have a harmful impact on the soils or the water bodies of northern Thailand.
EFFECTS ON THE UPLAND RICE CROP

7

14

21

28

Days after spraying
2. Changes in the mean (n = 4) electric conductivity of the topsoil (0–5 cm) of soil sediments and of (undiluted) runoff water following the application of an herbicidal salt solution (300 kg NaCl ha–1) in an upland rice field (slope = 30%) cultivated for 2 successive years. Mae Sa Mai station Thailand, 1995 and 1996 WS.

In case of high application rates (1,000 kg NaCl ha–1) and 2 to 3 successive applications, we observed an increase of both soluble and exchangeable Na in the soil, as well as an increase in pH. No effects on soil physical parameters, such as penetration resistance, shear strength, and micro-aggregate stability, were observed. These findings are consistent with soil science theory. Of all soil cations, Na is the one that is least strongly attached to soil colloids. Soils on sloping

The on-farm study of salt application did not reveal effects of salt on the upland rice crop because of the extensive variability of the crop environment and cropping practices between fields. According to the literature, moderate amounts of Na and Cl can stimulate the growth of certain plants under specific soil and climate conditions. Some plants can substitute a proportion of the K in their tissues with Na, which is thought to stimulate cell expansion and to improve the water balance of plants when water supply is limited. A significant increase of the rice straw biomass was observed in one pot experiment at application rates of 300 and 1,000 kg NaCl ha–1. The conclusions drawn from our study: q The method can effectively (though temporarily) control A. conyzoides and other Asteraceae weeds. q In the pedo-climatological and farming context of northern Thailand, the method does not seem to have major short- or long-term

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harmful effects on either soil or the upland rice crop. q Other common inorganic water-soluble fertilizers can similarly be used as postemergence contact herbicides against Asteraceae weeds. This case study also shows that farmers actively experiment and that their innovations are interesting research topics. More research with different farming and environmental conditions is required prior to promoting salt or common inorganic fertilizers as alternative herbicides in upland rice or other crops.

ANR(%) = (TNUP – TNUPO)/Nappl × 100 = ∆TNUP/Nappl

where TNUP is total N uptake (kg ha–1) in N applied plot, TNUPO is total N uptake (kg ha–1) in no-N plot, ∆TNUP is the increase in total N uptake by N application (kg ha–1), and Nappl is N application rate (kg ha–1). In addition, the following parameters were used for the analysis of internal N use efficiency and grain yield determination:
GYNUE = GY/TNUP = (TDW × HI × 100/86)/NUP = PNUE × HI × 100/86

Improvement of N use efficiency with the use of controlled-release N fertilizer in upland rice in eastern India M. Kondo, R. Agbisit, and C.V. Singh Understanding the impact of N input on yield and the interaction process with water supply is needed to develop efficient N management strategy for rainfed upland rice. Split application has been recommended as a way to improve N recovery by supplementing N after active tillering. However, timing of N application must accurately meet demand by the rice plant, and that is often not feasible because of unpredictable rainfall. A resin-coated, controlled-release N urea with temperature-dependent N release was recently developed. We did field experiments to quantify and compare variability in N recovery and internal N use efficiency from use of split applications of urea and controlled-release urea (CRU) in relation to rainfall. The experiments were at the Central Rainfed Upland Rice Research Station (CRURRS) in Hazaribag, Bihar, India, during 1995-97 WS. Vandana, an improved short-duration variety was used. The soil was Udic Rhodudalfs (pH (H2O) = 5.0). N application was as split applications 15, 30, 45, and 60 d after sowing (DAS) with urea at 35 (USP35), 70 (USP70), and 105 (USP105) kg N ha– 1 and basal application of CRU at 105 kg ha –1 (CRU105). CRU was applied as a band in the furrow at seeding. Total rainfall during the crop season varied from 595 mm in 1996 to 1,053 mm in 1997. Apparent N recovery (ANR) was calculated to estimate N recovery from applied N fertilizer as follows:

where GYNUE is N use efficiency for grain yield (kg kg–1), GY is grain yield at 14% moisture (kg ha–1), TDW is total aboveground biomass (kg ha–1), HI is harvest index, and PNUE is physiological N use efficiency for dry matter production (TDW/ TNUP) (kg kg–1). Agronomic N use efficiency (ANUE) for determining N application efficiency for increasing GY is defined as follows:
ANUE = (GY- GYO)/Nappl = ∆GY/∆TNUP × ANR

where ∆GY is the increase in GY by N application (kg ha–1).
FACTORS AFFECTING GRAIN YIELD

Results of ANOVA (Table 10) showed that sums of squares (SS) associated with year accounted for the large portion (47.7%) of SS in the yield, indicating the importance of N input in determining yield. At the same time, the importance of the effect of year and the interaction of year × N management in determining grain yield was also indicated. The complexity in evaluating the beneficial effect of N on yield was derived from fluctuations in both TNUP and GYNUE. TNUP was largely affected by N and, to lesser extent, by year × N management. GYNUE was largely affected by year and not significantly affected by N management because PNUE and HI were affected more by the year than by N management. HI varied among years by 19% and PNUE by 20%.

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Table 10. Grain yield, total N uptake (TNUP), harvest index (HI), physiological N use efficiency (PNUE), and grain yield N use efficiency (GYNUE) as affected by year and N management in field experiments at CRURRS, Bihar, India, 1995-97. Treatment Grain yield (t ha–1)a 1995 1996 1997 LSD(y)(p=0.05) No N USP35 USP70 USP105 CRU105 LSD(N management) (p=0.05) df 1.6 1.9 2.9 0.31 1.2 1.9 1.7 2.1 2.72 0.63 Mean square (×102) Year Rep in Year N management Year × N management Residual Total 2 9 4 8 36 59 1.53** 0.19 3.82** 0.45 0.23 0.54 Sums of square (%) 9.6 5.4 47.7 11.2 26.2 100.0 0.49 0.65 19.59** 2.30** 0.72 2.20 (×102) 14.29** 1.17 1.21 1.00 0.85 1.40 0.029* 0.005 0.005 0.004 0.003 0.004 (×102) 44.63** 3.40 2.19 1.70 2.58 3.99 TNUP (kg ha–1) 37.0 35.1 38.2 5.8 24.1 30.6 31.8 40.4 57.2 14.3 GYNUE (kg kg–1) 43.4 54.4 60.0 7.8 51.8 55.8 53.8 54.0 47.5 9.4 HI PNUE (kg kg–1) 107 110 134 13 111 116 122 120 116 12

Year

0.35 0.43 0.38 0.05 0.40 0.41 0.38 0.38 0.36 0.06

N management

Source of variation

Year Rep in Year N management Year × N management Residual Total
a

0.8 4.5 60.5 14.2 20.1 100.0

34.6 12.8 5.9 9.7 36.9 100.0

23.4 18.5 8.6 12.4 37.2 100.0

38.0 13.0 3.7 5.8 39.5 100.0

*, ** = indicate significant F values at p = 0.05 and 0.01.

Yield without N averaged 1.2 t ha–1 and varied from 0.90 to 1.5 t ha–1 (Fig. 3). Application of N increased yield in all 3 years although not significantly in 1995. Mean grain yield over the 3 years with CRU (2.7 t ha–1) was 21% higher than that with USP (2.1 t ha–1) at 105 kg N ha–1. CRU, in particular, gave significantly higher grain yield than USP in 1997. Grain yield was linearly correlated with TNUP across years (Fig. 4). The correlation between TNUP and yield was higher within year than across years, which indicated that TNUP was primarily an important determinant for yield particularly within the same year. The yield relative to TNUP was slightly lower in 1995 than the other 2 years because of lower HI as the dry period coincided with the flowering stage. Low HI in 1995 was

Grain yield (t ha–1) 4. 03 .5 3. 02 .5 2.0 1.5 1.0
No US N P US 35 US P70 P CR 105 U1 05 No US N P US 35 US P70 P CR 105 U1 05 No US N P US 35 US P70 P CR 105 U1 05

1995

1996

1997

N management 3. Effect of N management on rice yield in experiments with split applications (4) of N at 35 kg urea (USP35), 70 kg urea (USP70), 105 kg urea (USP105), and 105 kg controlled-release urea (CRU105) ha–1. CRURRS, Bihar, India, 1995-97.

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IRRI program report for 2000

Grain yield (t ha–1) 3.50 3.00 2.50 2.00 1.50 1.00 0.50 0.00 0.0
1995 1996 1995:y = 0.0393x + 0.163 R2 = 0.956 1997 1997:y = 0.0447x + 0.3035 R2 = 0.808 1996:y = 0.0523x + 0.2155 R2 = 0.952 1997:y = 0.0402x + 0.6332 R2 = 0.968

20.0 40.0 TNUP (kg N ha–1)

60.0

80.0

4. The relationship between total N uptake (TNUP) and rice yield in experiments at CRURRS, Bihar, India, 1995-97.

ensuring N recovery in USP could be magnified with high rainfall, probably by enhanced leaching of NO3. ANUE was mainly determined by ANR with the data of all 3 year (R2 = 0.832). ANUE in CRU (14.1 kg kg–1) was higher than that in USP at the same N rate (105 kg N ha–1) in all years. Root length density tended to increase with N below 45 cm depth (Fig. 6). CRU increased root length density from the surface layer to the layer below 60 cm. The vertical distribution was deeper with N than with no N. Fraction of root length below 30 cm, compared with total root length to 90 cm depth was 26.5% for no N, 33.8% for USP at 105 kg N ha–1, and 31.6% for CRU at 105 kg N ha–1. It is possible that the increase in root length density in deep soil layers helps to exploit water.
STRATEGIES FOR IMPROVING PRODUCTIVITY

ARN (%) 50 40 30 20 10 0

1995

1996 N management

1997

The results indicated the significance of N input for the improvement of productivity of upland rice when N recovery from N application is ensured. The highest recorded GYNUE (60 kg kg–1) was comparable with the value generally obtained in irrigated lowland. Continuous N supply (e.g., by CRU) can be an effective option to improve and stabilize ANR and yield in areas with variable rainfall patterns. Total profitability from the use of controlled-release N fertilizer must be evaluated with long-term
Depth 0.00 1.00 2.00

US P3 US 5 P US 70 P1 CR 05 U1 05

US P3 US 5 P US 70 P1 CR 05 U1 05

5. Effect on N management on apparent N recovery (ANR) in experiments with split applications (4) of N at 35 kg urea (USP35), 70 kg urea (USP70), 105 kg urea (USP105), and 105 kg controlled-release urea (CRU105) ha–1. CRURRS, Bihar, India, 1995-97.

US P3 US 5 P US 70 P1 CR 05 U1 05

0–15 cm 15–30 cm 30–45 cm 45–60 cm 60–75 cm 75–90 cm 6. Effect of N management on root length density (RLD) in soil layers in 1997 season for experiments with split applications (4) of N at 35 kg urea (USP35), 70 kg urea (USP70), 105 kg urea (USP105), and 105 kg controlled-release urea (CRU105) ha–1. Bars indicate LSD (p=0.05) among treatments. CRURRS, Bihar, India, 1995-97.
No N USP35 USP70 USP105 CRU105

associated with limited increase in total dry weight from flowering to maturity probably due to high spikelet sterility and poor panicle exsertion.
NITROGEN RECOVERY AND ROOT GROWTH

ANR with CRU tended to be higher than, or comparable with, that with USP in all 3 years (Fig. 5). On an average of 3 years, ANR in CRU was 31.5% while that in USP ranged from 11.1 to 18.6%. Difference between CRU and USP in ANR tended to be relatively large in 1997 because of low ANR in USP when there was highest rainfall. Difficulty in

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61

assessment on yield stability, impact on the environment, and operational cost in different farming system. On the other hand, substantial year-to-year variations of HI and PNUE was assumed to be due to unstable water capture under low-water stress, which would be difficult to overcome by management. Further genetic improvement in the deep rooting trait will be useful to improve capture of water and decrease leaching loss of N.

Upland Rice Research Consortium (URRC)
Workshops Long-Term Phosphorus Experiment Workshop, 28 Aug-1 Sep 2000. The Long-Term Phosphorus Experiment (LTPE) network, established in 1994 under the Upland Rice Research Consortium (URRC), is operational at 1) Siniloan and 2) Matalom, Philippines; 3) Sitiung, Indonesia; 4) Fang, Thailand; 5) Hazaribag, India; and 6) Thai Nguyen, Vietnam. The workshop objectives were to 1) analyze, synthesize, and interpret results from each LTPE site; 2) generate P coefficients to generalize results to similar soil and production conditions; 3) apply P coefficients from the LTPE to evaluate P decision aids for Asian uplands; and 4) develop country synthesis papers on P management research in the uplands. During the workshop, the LTPE network researchers compared and summarized their data in hands-on computer sessions and later made a joint synthesis presentation at the URRC Annual Review Meeting, 4–8 Oct 2000. The participants learned how to synthesize LTPE results into coefficients that could be used to generalize results to similar soil and cropping conditions, how to check LTPE results with predictions by P decision aids such as NuMaSS being developed by the University of Hawaii Soil Management Collaborative Research Support Program, and how to develop experiments that test predictions of the decision aid. The teams agreed to prepare synthesis papers on the status and prospects of P research in the uplands in their respective countries (to be published as part of workshop proceedings) and develop new action plans for the LTPE for the next 2–3 years. Aerobic Rice Workshop, 7-8 Sep 2000. The workshop reviewed the state of development of aerobic rice technology, its characteristics and

potentials, and attempted to define a research agenda for the development of aerobic rice in Asia. Aerobic rice is a system of rice production wherein the crop is direct seeded, the soil is not puddled, bunds may or may not be present, and there is no standing water or soil saturation during the growing season. The crop may be rainfed, supplementary irrigated, or fully irrigated. Irrigation is applied only to bring the soil water content up to field capacity after soil moisture has reached a certain lower threshold level. Irrigation techniques vary from furrow and basin to sprinkler and drip systems. Because aerobic rice is potentially more waterefficient than lowland rice, it is an attractive alternative in rainfed areas and in irrigated areas that suffer from water shortage. Workshop on commercialization, land use changes, and food security in the uplands of northern Vietnam, 28-29 Sep 2000. The workshop was organized by the IRRI Social Sciences Division and the Thai Nguyen University and held in Thai Nguyen, Vietnam. A preliminary output of an ongoing study on commercialization and its effect on food security in uplands was presented and the future role of upland rice for enhancing the regional food security in Vietnam was discussed. Fifty people representing national and regional policymakers and researchers participated. Ten papers on socioeconomic aspects of upland rice systems and policies for upland development were presented. Discussions that ensued focused on the importance of improving the productivity of upland rice for assuring food security of upland farmers, even though Vietnam now has achieved the status of a major rice exporter. Limited access to markets and the lack of income to purchase rice in the market in remote areas were recognized as the major factors that have forced upland farmers to become as self-sufficient in rice as possible. Participants considered upland rice to be an important component of the livelihood strategy of upland farmers even though its share in the total rice output of Vietnam now is low. Increasing the productivity of upland rice was seen as an important strategy to improve the food security of povertystricken upland farmers and to release land and labor for diversification into other income-generating activities.

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Progress of unreported projects
Genetic improvement of upland rice Efficient breeding system for drought-prone environments
q

was completed using both laboratory bioassays and greenhouse screenings. The mapping population AC1423/Aus196 was genotyped using 140 microsatellite markers. Genetic variability of major pests and host resistance with focus on blast and nematodes
q

q

q

q

q

q

Yield data for INGER International Upland Rice Observational Nurseries for the years 1995-99 were analyzed across sites in Asia. Two broad target environments for the IRRI upland rice breeding program were identified: 1) South Asian regions with neutral soils where short-duration, aus-type materials are preferred and 2) Southeast Asian acid uplands, where longer duration cultivars are preferred. Combined analyses of DS trials of IR64/ Azucena recombinant inbred lines over 3 years indicated that grain yield under continuous, moderate drought stress is at least as heritable as most secondary traits thought to be associated with drought tolerance. Drought tolerance screening in the IRRI upland rice breeding program will emphasize direct selection for grain yield under managed drought stress. An aerobic rice breeding program was initiated, with the objective of producing upland cultivars with high yield potential when grown with favorable conditions and intensive management. Studies were completed to identify QTLs associated with grain set under reproductivestage stress in the Azucena/Bala and IAC135/ Co 39 mapping populations. Among 58 IR64 lines introgressed with Azucena alleles through marker-assisted selection, seven were identified with superior performance in upland conditions with stress at flowering. QTLs were identified for osmotic adjustment in backcross progeny of IR60080-46A (improved upland japonica) introgressed with random alleles from IR62266 (improved rainfed lowland indica).

q

Sixteen advanced backcross lines in Vandana background with introgressed resistance from Moroberekan were selected and characterized based on association with candidate genes for disease resistance. Significant correlation was found between seedling and neck blast resistance for the 16 lines in greenhouse and blast nursery tests. Lesion number and lesion density was identified as the most important predictors of quantitative resistance to blast. An initial screen of 60 Oryza longistaminata accessions was done for nematode resistance. Preliminary results indicate genotypes with resistance to M. graminicola.

Perennial upland rice
q

q

q

Allelopathy and competitive ability
q

q

Phenotyping of the mapping population AC1423/Aus196 for its allelopathic potential

O. sativa/O. longistaminata and O. sativa/O. rufipogon progeny planted in 1999 WS were evaluated for perenniality, fertility, and drought tolerance in upland fields. Strong stolon production was observed in some O. sativa/O. rufipogon progeny. Excellent perenniality and fertility was found in many O. sativa/O. rufipogon F1 progeny, suggesting that the goal of developing perennial upland rice is readily feasible. Experiments were initiated to study source and sink capability in perennial interspecific progeny. Preliminary results indicate that some O. sativa/O. rufipogon progeny have high levels of photosynthesis, which would have broad implications for all rice ecosystems. O. sativa/O. rufipogon progeny were evaluated for variation in membrane stability and inheritance of that trait. We placed 148 markers on an O. sativa/ O.longistaminata mapping population to identify QTLs for rhizome expression.

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63

Grain quality traits
q

Genes for aroma were backcrossed from a Basmati source into a broad range of improved upland recurrent parents. About 200 BC1- or BC 2 -derived aromatic lines are ready for agronomic evaluation by NARES, and will be increased for distribution in 2001.

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IRRI program report for 2000

Research programs Cross-ecosystems research

FUNCTIONAL GENOMICS 68 Production and characterization of mutants 69 Development of introgression lines to capture useful alleles from diverse germplasm of cultivated rice 69 Development and characterization of align introgression lines 70 Development of new recombinant inbred populations and substitution lines 70 Understanding physiological stages critical for tolerance for drought stress 71 Molecular cloning and expression of stress-responsive elF1 gene in Porteresia coarctata Tateoka 73 Proteomic analysis of rice leaves exposed to drought and rewatering 73 Genetic dissection of disease-response pathways 74 Bioinformatics and databases 74 Web interface for the mutant database 74 CGIAR-national center for genomic resources collaboration 74 Stress genes database for functional genomics of abiotic stress 74 International Rice Functional Genomics Working Group 75 APPLYING BIOTECHNOLOGY TO ACCELERATE RICE BREEDING AND BROADEN THE RICE GENE POOL 75 Molecular characterization of introgression from O. glaberrima 75 Production and characterization of doubled haploids from anther culture of F1s of O. sativa/O. glaberrima 75 Asian Rice Biotechnology Network: advancing marker-aided selection products with disease and insect resistance 77 Evaluation of marker-aided selection products 77 Improved gene markers for selection 77 Training workshops to improve technical skills 77 Analysis of quantitative blast resistance by association genetics 78 Marker-aided selection for gall midge resistance 78 Genetic basis of inbreeding depression and heterosis in rice 79

International rice molecular breeding program for massive introgressison of desirable QTLs into elite genetic backgrounds 80 Identification of QTLs for disease resistance and important agronomic traits 80 QTLs for lodging resistance and plant development traits in rice 80 QTLs for traits associated with the primary sink size and grain milling quality in rice 81 QTLs for quantitative resistance to bacterial blight in rice 81 Anther culture 82 Transformation 82 Enhanced resistance to sheath blight from various transformation methods 82 Increasing the efficiency of rice transformation 83 Biological nitrogen fixation 84 Colonization of rice by diazotrophic endophytes 85 Genetic predisposition of rice for forming symbiosis with rhizobia 85 EXPLOITING BIODIVERSITY FOR SUSTAINABLE PEST MANAGEMENT 85 Impact on farmer income of varietal mixture planting 86 Durability of the Xa7 gene for bacterial blight resistance 86 RICE: A WAY OF LIFE FOR THE NEXT GENERATION OF FARMERS 88 Assessment of milled rice quality in the Philippine retail market 88 SOCIOECONOMIC STUDIES FOR TECHNOLOGY IMPACT, GENDER, AND POLICY ANALYSIS 88 Recent changes in Thailand’s rural economy: insights from a repeat survey of six villages 88 Changes in resource base and technology for agriculture 89 Structure and growth of household incomes 89 Concentration of income and sources of income inequality 89

Livelihood and income distribution in favorable and unfavorable rice ecosystems in Bihar, India 91 Asset base and livelihood system 91 Structure and determinants of household income 91 Concentration of income and incidence of poverty 93 IMPLEMENTING ECOREGIONAL APPROACHES TO IMPROVE NATURAL RESOURCE MANAGEMENT IN ASIA 94 Exploring scenarios of rice supply and demand within a country 94 GIS modeling for rice yield and production estimation 94 Optimizing land use in South and Southeast Asia: a comparison of four SysNet case studies 97 Scenario construction and evaluation 97 Examples of scenario results: trade-offs between land use objectives 98 Expanded scenarios and what-if questions 99 PROGRAM OUTLOOK 99

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IRRI program report for 2000

Cross-ecosystems research

The Cross-Ecosystems Research Program develops knowledge and technology to solve problems common to different rice-growing ecosystems. The program works to solve current problems but is anticipatory and seeks opportunities to enhance ecosystem-based research. Research projects span the disciplines of biological sciences, natural resource management, and anthropological and socioeconomic analyses. One focus is to apply advances in biological sciences to develop practical ways to improve plant breeding and pest management and to explore opportunities in biological N2 fixation in rice. A biotechnology project involves the application of molecular and genetic tools to assist plant breeding. The Asian Rice Biotechnology Network (ARBN) works closely with national agricultural research systems (NARS) to develop improved rice germplasm that addresses local problems. Natural resource management work, through Systems Analysis and Simulation in Rice Production Systems (SysNet) research, examines the factors affecting technology adoption and the mechanisms needed to accelerate technology transfer to improve the livelihood of farmers. Social-economic research is concerned with how rice technology brings benefits to farmers and its impact on socioeconomic equity and poverty alleviation. Information for planning and prioritization of rice research is obtained from examination of trends in rice demand and pricing policies.

Functional genomics
The International Rice Genome Sequencing Project expects to have the entire rice genome sequence available to the public before 2004. IRRI’s Functional Genomics project has made progress toward the goal of producing genetic resources to capture the sequence information. We expanded the collections of mutants, introgression lines, substitution lines, and mapping populations in 2000. The lines have been subjected to systematic evaluation for a suite of biotic and abiotic stresses. The consolidation of phenotyping efforts on a common set of genetic resources has fostered teamwork and enhanced the documentation and interpretation of phenotypic data. A collection of disease-response mutants was established and genetic analysis of these mutants set the stage for dissecting disease-response pathways. Similarly, physiological and agronomic data on drought response traits were gathered as a prerequisite for understanding gene expression relevant to drought tolerance. A collection of stress-related expressed sequence tags was produced and is ready for array analysis. A bioinformatics team initiated activities to link phenotypes to genomic databases. An International Rice Functional Genomics Working Group was formed to establish a public resource platform. So far, 14 laboratories and institutions from around the world have participated to develop collaborative projects in functional genomics.

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Production and characterization of mutants H. Leung, D.S. Brar, P.Q. Cabauatan, C.Q. Guerta, G. Gregorio, G.J.D. Kirk, G.S. Khush, R. Lafitte, and C.M. Vera Cruz We advanced the collection of IR64 mutants using chemical and irradiation mutagenesis. As of December 2000, we had produced 18,400 M3/M3 lines and distributed them for phenotypic characterization for gain and loss of functions against biotic (diseases) and abiotic (submergence, salinity) stresses. About 6% of the lines were isolated to expand the stock of morphological mutants. We identified a suite of mutants with gain of resistance to bacterial blight and blast and 21 lesionmimic mutants were isolated. Those mutants exhibit different levels of quantitative resistance. A total of 2,484 IR64 mutant lines were evaluated for resistance to tungro virus using the tray method of mass inoculation. Seven lines showed intermediate reaction (31–60% infection) while the rest were susceptible. Among the seven lines with intermediate reaction, six were tolerant. These lines will be subjected to microsatellite tests to confirm their genotypic identity. We initiated mutant screening for drought stress and submergence, salinity, and Zn deficiency tolerance. Quantitative variation was observed in Zn deficiency tolerance but no phenotypic variability for salinity stress (100 mM NaCl) was found in the initial screening. Phenotypic variation in submergence and drought tolerance was observed. About 3,000 M3 lines were field-screened for submergence tolerance. Six putative mutants that give 75% recovery after 14-d submergence treatment at the seedling stage were identified. Seeds from those are being reevaluated to confirm inheritance of submergence tolerance and yield performance. In 1999, 1,200 IR64 mutant lines were evaluated for yield with continuous flooding and with floodwater drained prior to flowering. We identified 65 lines with superior yield in either the stress or the control treatment. An additional 1,200 lines were evaluated in 2000. They were uniform in appearance and flowering date with some variation in senescence rate observed under stress. Based on

visual scores and grain yields under stress, 26 lines were identified for further assessment of variation in component traits related to tolerance for late-season stress. Development of introgression lines to capture useful alleles from diverse germplasm of cultivated rice Z. Li, S.B. Yu, W.J. Xu, J. Ali, Vijayakumar, J. Domingo-Rey, R. Maghirang, C. Aquino, R. Lafitte, and G.S. Khush We advanced two sets of near-isogenic introgression lines (NIILs) in the genetic backgrounds of IR64 and new plant type (NPT) IR68552-55-3-2 by backcrossing. Selective and random introgression was used. In selective introgression, 200 donors of diverse origins were selected and used as donors for the introgression. Crosses and backcrosses were made during 2000 WS to introgress genes-quantitative trait loci (QTLs) affecting a wide range of phenotypes into the IR64 and NPT genetic backgrounds (Table 1). A replicated experiment in 2000 DS characterized the field performance of 180 donor cultivars in four contrasting water regimes—fully irrigated lowland, lowland with water removed at 73 d after sowing (DAS), aerobic soil with furrow irrigation twice a week, and aerobic soil with furrow irrigation once a week. Most of the cultivars were adapted to lowland cultivation and performed much better in the fully irrigated lowland field, even with stress, than in the aerobic soil (Table 2).

Table 1. Status of backcross populations developed for two recurrent parents. IRRI 2000 WS. Backcross generation BC2F2 populations BC3F1 lines BC2F1 populations BC2F1 lines BC1F2 BC1F1 Recurrent genotype Introgression NPT Random Selective Random Selective 62 1,650 63 450 60 60 IR64 64 750 64 500 77 77

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Table 2. Evaluation of germplasm with potential to confer drought tolerance in introgression lines. IRRI, 2000 DS. Environment Days to 50% flowering 82 83 86 88 Yield average t ha–1 (range) 3.1 (0.3 – 6.8) 2.5 (0.1 – 5.4) 0.6 (0 – 3.6) 0.3 (0 – 1.8) Best five cultivars (origin)

Lowland, irrigated Lowland, drained Aerobic, irrigated 2× wk–1 Aerobic, irrigated 1× wk–1

IR68835-28-2-B-1 (IRRI), Ajaya (India), Chorofa (Philippines), Jiangxi-Si-Miao (China), CS94 (Vietnam) OM1723 (Vietnam), HR98 (India), BG300 (Sri Lanka), CS94 (Vietnam), ASD16 (India) PSBRc 28 (Philippines), PSBRc 66 (Philippines), ASD18 (India), C70 (Vietnam), CS94 (Vietnam) IRAT216 (Côte d’Ivoire), TKM9 (India), Rubio (Peru), Doddi (India), Madhukar (India)

BC2F2 bulks from selected donors will be evaluated under water deficit in lowland and upland fields to select plants with superior alleles for conditions of water deficit. Those plants will be backcrossed to the recurrent parent before another cycle of selection. Development and characterization of alien introgression lines D.S. Brar A series of alien introgression lines were produced to extract useful alleles from the Oryza gene pool. Embryo rescue and direct crosses were used to produce a series of hybrids between elite breeding lines of rice and several wild species (Table 3). In addition, monosomic alien addition lines (2n=25) and introgression lines (2n=24) were produced from various cross-combinations. Recombinant inbred lines (RIL) were produced from the cross IR64/O. rufipogon. IRRI-WARDA collaboration produced a large number of introgression lines from crosses of O. sativa/O. glaberrima. O. glaberrima is low yielding but has several useful traits such as resistance to rice yellow mottle virus, African gall midge, and nematodes and tolerance for abiotic stresses such as drought, aluminum toxicity, iron toxicity, P deficiency, and acid soil. Introgression lines derived from O. sativa/O. officinalis, O. sativa/O. australiensis, O. sativa/O. minuta, O. sativa/O. brachyantha, and O. sativa/O. granulata show introgression of small chromosome segments from wild species into the cultivated rice genome and resemble the recurrent rice parent in morphological characters. Several advanced lines derived from the cross NPT/O. longistaminata were identified as showing introgression for bacterial

blight resistance, earliness, large panicle, and increased seeds per panicle. Development of new recombinant inbred populations and substitution lines Y. Fukuta, H. Sasahara, K. Tamura, and T. Fukuyama Recombinant inbred populations are useful resources for evaluating multiple quantitative traits. We produced F2, F5, and F11 populations generated from a cross between an indica type line, Milyang 23, and a japonica type variety, Akihikari. DNA marker linkage maps in each generation were developed. An F2 linkage map was developed using 119 restriction fragment length polymorphism (RFLP) markers in 202 F2 progeny. That map covered a total distance of 1,355 cM on the 12 rice chromosomes. Segregation of RFLP markers detected segregation distortions in 16 chromosome regions except for chromosomes 1 and 4. Among them, 10 chromosome regions showed an increased number of progeny with genotypes of indica and four chromosome regions showed an increased number of progeny with genotype japonica homozygotic alleles. Two other regions showed an increase in indica/japonica heterozygotes. Skew in favor of indica alleles was detected on chromosomes 2 and 3 (two regions); 5, 6, 9, and 11 (two regions), and 12 (two regions); and that of japonica on chromosomes 7, 8, and 10 (two regions). An increase of heterozygotes was detected on chromosomes 2 and 9. In addition to RILs, we advanced the development of substitution lines with Akihikari genetic background. A total of 185 lines of (Milyang 23/ Akihikari RIL/Akihikari) (BC1F3) and (Milyang 23/

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Table 3. Status of alien introgression lines produced from crosses of rice and wild species. IRRI, 2000. Target trait(s) Cross combination Population produced Transferred into O. sativa Progenies under evaluation

O. sativa (recurrent parent) IR64

Wild species (donor parent) O. rufipogon (AA)

Elite breeding lines BC2/BC3F3-F8 RIL New CMS line New CMS line BC2/BC3F3-F5 BC1F3,BC2F2 BC2/BC3F3-F6 Elite breeding lines BC2/BC3F3 BC2/BC3F3 Elite breeding lines BC2/BC3F3-F8 BC2/BC3F3-F8 Elite breeding lines BC2/BC3F3-F8 Elite breeding lines BC2/BC3F3-F6 BC2/BC3F3-F6 BC2F1

Tolerance for tungro –

IR64 IR64 IR64, BG90-2 Several O. sativa IR65600-81-5-3-2 (NPT) IR31917-45-3-2 M202 IR65600-81-5-3-2 (NPT) IR31917-45-3-2 IR31917-45-3-2 IR31917-45-3-2

O. perennis (AA) O. glumaepatula (AA) O. glaberrima (AA) O. glaberrima accessions O. longistaminata (AA)

CMS CMS – – BB

O. officinalis (CC) O. officinalis (CC) O. officinalis (CC) O. minuta (BBCC) O. latifolia (CCDD) O. australiensis (EE)

BB, BPH, WBPH – – BB, BPH, blast – BB, BPH BB, BPH

– Increased yield potential Tolerance for abiotic stresses – – Tolerance for biotic and abiotic stresses Tolerance for biotic and abiotic stresses Tolerance for biotic stresses, increased yield potential – Resistance to sheath rot Resistance to BB, tungro – Resistance to sheath blight – – Tolerance for abiotic stresses – Resistance to stem borer Resistance to BPH Tolerance for tungro, resistance to stem borer

IR56 IR31917-45-3-2 IR56

O. brachyantha (FF) O. granulata (GG) O. ridleyi (HHJJ)

BB – –

Akihikari RIL/Akihikari) (BC1F 2/Akihikari F1) were bred. Substitution lines will be selected with the aid of RFLP and simple sequence repeat (SSR) markers. Development of the RILs and substitution lines using japonica/indica RI derivatives will provide resources for QTL analysis of agricultural traits derived from japonica/indica hybrids. These lines will be particularly useful for clarifying the problems of wide hybridization and segregation distortion commonly observed in japonica/indica crosses. Understanding physiological stages critical for tolerance for drought stress R. Lafitte and J. Bennett Drought that occurs near flowering results in dramatic yield reduction in rice. Identification of the processes underlying spikelet sterility in the field is needed for understanding gene expression at the appropriate developmental stages. Experiments

were previously conducted to clarify the pattern of grain formation in genotypes grown with different water regimes. We collected panicles from those experiments for preparation of cDNA libraries, which were used to add panicle-specific sequences to a rice-stress microarray. Three varieties were grown with three water regimes during 2000 DS: fully flooded lowland, aerobic soil maintained near field capacity by drip irrigation 3 times wk–1, and aerobic soil with a 2-wk water exclusion period ending about 5 d after anthesis. The varieties included the lowland cultivar IR64 and two upland-adapted improved cultivars, IR55435 and IR55411. Previous observations indicated that IR55435, which includes an aus parent, is less sensitive to drought stress at flowering than IR55411, and both lines outperform IR64 under water deficit. In the lowland field, both upland varieties had more spikelets per tiller than IR64. In the aerobic

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fields, IR64 and IR55411 produced significantly fewer spikelets per panicle than in the lowland field, but the number of spikelets per panicle in IR55435 was largely unchanged except on the latest tillers (Fig. 1). The fraction of spikelets that formed filled grains (% fertile spikelets) was less for IR55435 than for the other lines in the lowland field (Fig. 2). IR55435 maintained spikelet fertility at similar levSpikelets panicle–1 (no.) 180 160 140 120 100 80 60 40 20 0
Lowland Aerobic Stress

els in the lowland and well-watered aerobic fields. All three varieties showed a similar hierarchy among early, medium, and late tillers. In the lowland field, less than 20% of the spikelets without filled grains had been fertilized, indicating that most of the sterility observed was due to lack of fertilization. In the aerobic fields, about 50% of the unfilled spikelets had been ferti-

T1

T2

T1

55

55

55

55

55

IR

IR

IR

1. Number of spikelets per panicle for different classes of three genotypes grown in three water regimes. IRRI, 2000 DS.

Percent fertile spikelets 1.0

IR

IR

IR
Lowland Aerobic Stress

0.8

0.6

0.4

0.2

0

I

2. Spikelet fertility for different tiller classes of three genotypes grown in three water regimes. IRRI, 2000 DS.

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IR 55 41

IR

4 R6

IR 64 -T

64 -

1T

-T

1 IR 55 41 1T2 IR 55 41 1T3 IR 55 43 5T1 IR 55 43 5T2 IR 55 43 5T3

T3

1

2

55

I

IR

IR

4 R6

1-

1-

5-

64

64

1-

5-

41

41

43

41

43

43

5-

-T

-T

-T

T3

T2

T3

1

2

3

lized but then aborted. The results of this study will be used to develop a sampling strategy for genomic and proteomic studies of differences among genotypes and water regimes. Molecular cloning and expression of stressresponsive eIF1 gene in Porteresia coarctata Tateoka L. Rangan, M.S. Swaminathan12, G.S. Khush, and J. Bennett The halophyte Porteresia coarctata has mechanisms for tolerating salt concentrations that would kill even the most salt-tolerant rice cultivar within 2 d (>150 mM). P. coarctata can be crossed with rice to form viable hybrids but they are not fertile, thus the salt-tolerance mechanisms cannot be transferred to rice by wide hybridization. We assessed the feasibility of transferring the salt-tolerance traits by molecular methods by examining gene expression in the halophyte after treatment with 150 mM NaCl. The most abundant double-stranded cDNA prepared from leaf mRNA of salt-treated halophyte was found to encode translational initiation factor 1 (eIF1). Expression studies showed that the abundance of eIF1 transcripts initially increased during 5 d of salt stress and then declined to control levels after 10 d of stress. The gene responded similarly when treated with 10 mM ABA or 700 mM mannitol, suggesting that its induction by 150 mM NaCl is related to the waterdeficit effect of high salt rather than the ion-toxicity effect. It is likely that increasing the salt tolerance of rice will involve enhancing its capacity to deal with both of these effects. We are exploring the possibility that eIF1 transcripts provide a convenient indicator for screening rice cultivars for the presence of the equivalent stress-responsive mechanism.

Proteomic analysis of rice leaves exposed to drought and rewatering S. Gh. Hosseini Salekdeh, L.J. Wade, and J. Bennett The rice germplasm contains many drought-tolerant accessions. We used proteomics to identify the various mechanisms of drought responsiveness and drought tolerance in leaves of plants undergoing vegetative-stage drought stress and then recovery after rewatering. Proteomics is a high-throughput technology in that it allows the response of more than 1,000 polypeptides to be digitally analyzed simultaneously on two-dimensional polyacrylamide gels and the identity of responsive proteins to be determined by mass spectrometric sequencing. The polypeptides are separated in the first dimension according to their isoelectric points and in the second dimension according to their molecular mass, and then visualized with silver staining. It is possible to detect responses that involve changes in the intensity of spots (up- or down-regulation), or in charge (e.g., phosphorylation), or in size (e.g., proteolytic or free-radical cleavage). Figure 3 shows the abundance of several proteins in one small region of two-dimensional gels for extracts of the top three leaves of rice plants that were either well-watered, undergoing drought, or rewatered after drought. The abundance of most proteins did not change during stress or rewatering but the protein became increasingly abundant by the time the drought-stressed plant had transpired 3 kg of water (Fig. 3B) and 4 kg of water (Fig. 3C). The abundance of the protein declined in leaves of rewatered plants, being progressively lower after 5 d (Fig. 3D) and 10 d (Fig. 3E) of rewatering. The mechanisms governing these changes in protein abundance are under investigation. Mass spectrometric sequencing of the indicated protein provided enough sequence

A

B

C

D

E

3. Two-dimensional polyacrylamide gel electrophoresis (PAGE) of leaf proteins from plants well watered (A) or undergoing drought (B and C) followed by rewatering (D and E) after-drought equivalent to (C). The same small area of each silver stained gel is shown. Isoelectric focusing is from right to left and SDS-PAGE is from top to bottom. IRRI, 2000.

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to allow isolation of the corresponding gene but did not resemble the sequence of any known protein. Genetic dissection of disease-response pathways H. Leung, C.M. Vera Cruz, and J. Leach Understanding the genetic steps controlling diseaseresponse pathways provides the basis for identifying genes with high contribution to resistant phenotypes. We isolated and produced single- and doubledisease mutants to dissect the disease-response pathways. Seven double mutants were produced to identify genes involved in different steps of the disease-response pathways. Double-lesion mimic mutants demonstrated enhanced resistance to both bacterial blight and blast. Gene expression analysis of these mutants suggested that mis-regulation of certain defense-related genes was correlated with the resistant phenotypes. An extended panel of candidate genes is being used to correlate gene expression with broad-spectrum disease resistance. In addition to mutational analysis, disease-resistance candidate genes were used to establish association between candidate gene profiles and phenotypic performance in different breeding populations. We produced pathogen-induced subtractive cDNA libraries to generate a collection of candidate genes involved in stress-response pathways. Partial sequencing of those yielded 150 unique sequences. In addition, candidates of major resistance genes, a collection of nucleotide binding site-leucine rich repeat (NBS-LRR) sequences, was established by database mining. Allelic variants of NBS-LRR sequences (oxalate oxidase ion-channel regulator) were found to be strongly associated with breeding lines of the resistant phenotype. This collection of consensus candidate genes represents potential predictive markers applicable to disease-resistance breeding programs. Bioinformatics and databases R. Bruskiewich, G. McLaren, K. McNally, and H. Leung
WEB INTERFACE FOR THE MUTANT DATABASE

and molecular data on the IR64 mutant stocks. The ontology of component traits of mutant phenotypes is being defined to allow structured searches of the database. The mutant database currently has about 200 phenotypically described mutants. A prototype web interface (www.cgiar.org/irri/genomics/ index.htm) was implemented to allow users to search the database according to mutant phenotypes. The next phase of development will involve linking phenotypic data to molecular characterization of the mutants to facilitate the identification of candidate genes.
CGIAR-NATIONAL CENTER FOR GENOMIC RESOURCES COLLABORATION

IRRI, CIMMYT, CIAT, and CIP have joined in a collaborative project with the National Center for Genomic Resources (NCGR) in Santa Fe, New Mexico, to develop a comparative mapping tool, which will connect to ICIS databases via NCGR’s integrated software buss. This buss allows diverse applications and databases to interact in a dynamic manner, facilitating analysis of genomic and phenotypic data. The mapping tool will facilitate merging, linking, and filtering of genetic and physical maps with application in molecular breeding, functional genomics, and allele mining. Stress genes database for functional genomics of abiotic stress K. McNally, R. Bruskiewich, and G.L. Reyes Because relatively little is known about which genes correspond to QTLs involved in drought tolerance, we make use of existing sequence information to design polymerase chain reaction (PCR) markers targeted to stress-responsive QTLs. Keyword queries for general abiotic stress responses, regulatory features, or enzymatic functions are being used to search GenBank (via Entrez) and other public databases (via SRS5). So far, more than 22,400 stress-related sequences from 335 plant species have been recovered with 2,300 of those from rice. StressGenesDB, an AceDB-based database, is being developed to facilitate the use of these sequences. The hierarchical, object-oriented design and querying features of AceDB allow easy restructuring of data into meaningful groups. The current version of StressGenesDB is at an early stage of

The International Rice Information Systems (IRIS) database is used to manage genealogy, phenotype,

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development (beta release 0.2). The database will serve as a common link between different research groups working in abiotic stresses. International Rice Functional Genomics Working Group H. Leung, G.S. Khush, and K.S. Fischer The International Rice Functional Genomics Working Group was established to broaden access to genetic resources and to accelerate gene discovery in rice. Priorities of the Working Group were developed through a series of international meetings. A number of groups from the research community agreed to contribute resources and expertise to three activities: q information node with phenotype databases and links between research groups (www.cgiar.org/irri/genomics/index.htm), q sharing of genetic stocks, and q developing resources for microarray analysis.

Transformation was used to introduce key genes for resistance to bacterial, fungal, and insect pests and field tests of the transformants were successfully conducted in China. Since its inception in 1993, the Asian Rice Biotechnology Network (ARBN) has enabled scientists from national agricultural research and extension systems (NARES) and IRRI to share biotechnological tools, resources, and products through collaborative research, backed by training and shuttle research at IRRI and training and troubleshooting incountry.
q

Molecular characterization of introgression from O. glaberrima J. Talag, Zhikang Li, and D.S. Brar We have produced a large number of advanced backcross progenies from the crosses of elite breeding lines of O. sativa with different accessions of O. glaberrima. A subset of 95 mapped microsatellite markers was used for polymorphism survey of two accessions of O. sativa and 14 accessions of O. glaberrima. A high degree of polymorphism was observed, with 67 out of 95 markers (70%) polymorphic between O. sativa and O. glaberrima, while 28 markers (30%) showed polymorphism among O. glaberrima accessions. Advanced backcross lines with O. sativa as recurrent parent (BC2F3 and BC4F3) were characterized for introgression. Of the 67 polymorphic markers, 31 markers detected introgression from O. glaberrima into O. sativa. The introgressed segments of O. glaberrima were found in homozygous as well as in heterozygous forms in these lines. Production and characterization of doubled haploids from anther culture of F1s of O. sativa/O. glaberrima E. Enriquez, D.S. Brar, M.T. Jones, and G.S. Khush We are attempting to combine the high productivity of O. sativa with the tolerance for biotic and abiotic stresses of O. glaberrima. O. glaberrima is lowyielding but has useful genes for resistance to rice yellow mottle virus, African gall midge, nematodes and a good level of tolerance for abiotic stresses such as drought, iron and aluminum toxicity, and phosphorus deficiency. It is also an important

Applying biotechnology to accelerate rice breeding and broaden the rice genepool
The efficiency and scope of rice breeding can be increased and the genepool of valuable traits can be broadened by access to biotechnology tools, including DNA marker technology, anther culture, wide hybridization, transformation, and gene discovery through functional genomics and proteomics. Significant advances were made in the last 12 years: q Genes for resistance to brown planthopper (BPH), bacterial blight (BB), and blast were transferred across genetic barriers from wild species into rice. q We determined the position of rice centromeres on the RLFP map of the rice genome. q Genes for resistance to tungro virus, BB, BPH, gall midge, and green leafhopper, and those regulating aroma, plant height, salt tolerance, submergence tolerance, photoperiod sensitivity, and traits associated with drought tolerance were mapped. q Multiple genes for resistance to BB and blast were pyramided through molecular marker technology for durable resistance against these pests.

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source of weed competitiveness. The two species show strong reproductive barriers and their F1 hybrids exhibit high level of sterility. Several sterility genes differentiate these two species. Anther culture was used to overcome sterility in such crosses and to produce homozygous lines, fix recombinants, and use such doubled haploid (DH) lines as mapping populations to locate genes governing agronomic traits. Using N6 medium, we cultured anthers of 75 F1s from crosses of 10 varieties of O. sativa with 18 accessions of O. glaberrima. The calli were transferred to MS medium supplemented with 1 mg L–1 each of BAP, kinetin, and NAA. After 3–4 wk, regenerated shoots were transferred to 1/4 MS medium devoid of any auxin. After 2–3 wk, the seedlings with well-developed roots were transferred to soil in pots. In general, the callus induction frequency was low—0.0–18.6%. We cultured 45,400 anthers from 75 F1s and did not obtain any calli from 34 crosses. The other 41 F1s showed an average 1.3% callus formation from 144,160 cultured anthers. Plant regeneration ranged from 0.0 to 77.0%. The anther-derived calli from 16 F1s did not show

any plant regeneration while callus induction and plant regeneration varied among genotypes in the remaining 25 F1s (Table 4). We produced 562 DH lines and characterized these lines based on plant morphology. We obtained 137 from IR68552-5-3-2/TOG 6589, 138 plants from IR68037-AC-24-1/CG14, and 65 plants from IR60080-46-A/CG14. Other crosses produced less than 30 plants each. Among O. sativa lines, an elite breeding line of NPT, IR68552-55-3-2, was found to respond better for producing green plants in crosses with O. glaberrima. Similarly, O. glaberrima accession CG14 in crosses with some of O. sativa parents responded favorably to anther culture. The DH lines had high (56–100%) seed sterility. High sterility of DH lines is indicative of the presence of several loci for sterility differentiating the Asian and African rice species. In view of such high seed sterility, we intend to produce DH lines from BC1F1 for effective utilization as mapping population. The results indicate strong genotypic differences for anther culturability both for callus induction and

Table 4. Callus induction and plant regeneration from anther culture of the F1s of O.sativa × O. glaberrima. WARDA and IRRI, 2000.

O. sativa/O. glaberrima
IR68552-5-3-2/CG14 IR68552-5-3-2/CG17 IR68552-5-3-2/CG20 IR68552-5-3-2/TOG 5675 IR68552-5-3-2/TOG 6472 IR68552-5-3-2/TOG 6589 IR68552-5-3-2/TOG 7235 IR68703-AC -24-1/CG14 IR68703-AC-24-1/CG17 IR68703-AC-24-1/TOG 6472 IR68703-AC-24-1/TOG 7235 IR60080-46A/IG10 IR60080-46A/CG14 IR55423-01/IG10 IR55423-01/TOG 5860 BG90-2/CG20 BG90-2/TOG 7442 IR68544-29-2-1-3-1-2/IG10 IR68544-29-2-1-3-1-2/CG14 IR65600-81-5-3-2/TOG 6589 IR65600-81-5-3-2/TOG 5674
a

Anthers F1 (no.)

Calli cultured (no.) 27 40 50 46 39 178 6 401 120 8 60 66 162 37 76 55 8 3 20 13 4
× 100.

Calli produced (%) 0.3 2.7 0.4 0.7 2.0 6.2 0.2 18.6 7.9 0.4 3.3 3.2 5.5 2.1 8.3 2.9 0.4 0.03 0.3 1.01 0.08

Plants regenerated (no.) 12 15 22 18 21 137 – 138 16 – 10 26 65 – 12 10 – – – – –

Plant regenerationa (%) 44.4 37.5 44.0 39.1 53.9 77.0 – 34.4 13.3 – 16.7 39.4 40.1 – 15.8 16.2 – – – – –

8920 1480 11880 6960 1960 2880 2840 2160 1520 2240 1800 2080 2960 1760 920 1920 2120 10600 6320 1280 4880

No. of plants regenerated Plant regeneration (%) = No. of callli plated

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IRRI program report for 2000

plant regeneration. Furthermore, callus induction and plant regeneration from anther culture were found to be independent of each other. Asian Rice Biotechnology Network: advancing marker-aided selection products with disease and insect resistance ARBN teams contributing to this research were Agricultural Genetics Institute, Vietnam (AGI); Central Rice Research Institute, India (CRRI); China National Rice Research Institute, China (CNRRI); Department of Agriculture, Thailand (DOA); Directorate of Rice Research, India (DRR); Guangdong Academy of Agricultural Sciences, China (GAAS); Indira Gandhi Agricultural University, India, (IGAU); Punjab Agricultural University, India (PAU); Philippine Rice Research Institute, Philippines (PhilRice); Research Institute for Food Crops Biotechnology, Indonesia (RIFCB); Kansas State University, USA (KSU); and IRRI. The ARBN has assisted NARS institutes in six countries to apply biotechnology tools for the development of locally adapted, high-yielding rice varieties with durable resistance against diseases and insect pests. Progress has been made toward testing marker-aided selection (MAS) products in farmer’s fields by several NARS teams. In year 2000, 23 improved lines tested at replicated yield trials, multilocation tests, or at farmers' fields underhigh disease or insect pressure showed less disease or gall midge infestation.
EVALUATION OF MARKER-AIDED SELECTION PRODUCTS

Xa7 showed high level of resistance to pathogens in trials at 23 sites. The PAU team evaluated a PR106 pyramid line carrying xa5+xa13+Xa21 for yield performance at six farmers’ fields at low disease pressure. Across farmer’s fields in Punjab, the three-gene pyramid lines yielded the same as the control PR106. All pyramid lines showed a high level of BB resistance (0.7–3.9 cm lesion) under high disease pressure in experimental plots. Plot yield was highest for line 1114-1 (xa5+xa13+Xa21) and line 1096-2 (xa13+Xa21), making them promising materials for field tests in 2001.
IMPROVED GENE MARKERS FOR SELECTION

We continued to expand a collection of cloned disease-response genes contributed by KSU. These new candidate genes were isolated from pathogeninduced cDNA libraries for rice, wheat, and maize and consist of NBS-LRR sequences, actin, phospholipases, peroxidase, thaumatin-like protein, glucanase, and light-induced proteins. IRRI has permission to distribute these new clones freely to NARS team members. CNRRI, AGI, RIFCB, and CRRI have applied these candidate genes as markers to incorporate quantitative traits for blast resistance in their popular commercial cultivars.
TRAINING WORKSHOPS TO IMPROVE TECHNICAL SKILLS

Five elite lines from PhilRice carrying xa5 and Xa21 in IR64 background showed little disease (<10% severity) at three disease hot spots in the Philippines. In the presence of the disease, the yield of the best line was 60% higher than IR64 without the resistance genes. PhilRice, with the aid of molecular markers, pyramided Xa4, Xa7, and Xa21 in two or three combinations in five maintainer lines for hybrid rice production and further advanced them to BC3F3 or BC3F2. Thirty-one elite lines in IR64 background carrying xa5, Xa7, and Xa21 were produced by RIFCB in Indonesia. Six of those elite lines carrying xa5 or

A total of 125 NARS scientists/students attended workshops at IGAU, CRRI, PAU, DOA, and AGI on applications of candidate genes, techniques and principles of MAS, and functional genomics. To improve skills and ope-ration at NARS institutes, 40 researchers were trained at DOA on techniques and principles of MAS. Four shuttle scientists (GAAS, PhilRice, AGI) conducted research at ARBN, complementing their research activities at home laboratories. Two new markers to increase selection efficiency, NBS-LRR (r10) for Pi1 and AFLP1415 for Xa7, have been developed as PCR markers, and were made available to AGI, RIFCB, and CRRI. CNRRI developed two new markers, A7 and K17, flanking a resistance gene effective against both leaf and neck blast on chromosome 6.

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Analysis of quantitative blast resistance by association genetics Bin Liu, Shaohong Zhang, Xiaoyuan Zhu, Qiyuan Yang, Shangzhong Wu, Mantong Mei, and H. Leung San-huang-zhan 2 (SHZ-2), an indica rice, exhibits durable resistance to blast based on International Rice Blast Nursery (IRBN) tests in different countries and performance in southern China. Work during 2000 was devoted to dissecting the genetic basis of blast resistance in SHZ-2 and introgressing its durable resistance to high-performing lines through MAS. A RIL population (n=250) was developed by single-seed descent using SHZ-2 (resistant) and Lijiangxin-tun-heigu (LTH, susceptible) as parents. Six representative isolates selected from different lineages and pathotypes in Guangdong, China, were used for the evaluation of complete and partial resistance in SHZ-2. Three major genes that controlled complete resistance to blast were found in SHZ2. The RIL population showed normal distribution in quantitative traits (disease leaf area, lesion number, and lesion size), suggesting that SHZ-2 has not only major genes conferring complete resistance but also minor genes that collectively confer a high level of partial resistance.
RI lines (no.) 20 18 16 14 12 10 8 6 4 2 0 1 3 8 13 18 23 28

Genetic control of partial resistance derived from SHZ-2 was examined by use of a panel of candidate genes to characterize the RILs without the major gene resistance. A total of 30 polymorphic RFLP markers consisting of NBS-LRR sequences (12) and defense-response genes (18) were used to develop DNA fingerprints of 105 lines. We hypothesized that lines with similar profiles of candidategene DNA would give a similar level of resistance. Random anonymous markers (30 SRR and 30 RFLP probes) were used as a control to characterize the same RILs. Results showed that candidate gene markers give a strong association between DNA fingerprints and phenotypic performance, whereas anonymous markers do not (Fig. 4). The data indicate the power of using candidate genes as selection tools for pyramiding quantitative resistance against blast. Marker-aided selection for gall midge resistance S.K. Katiyar, B.-C. Huang, and J. Bennett Asian rice gall midge (Orseolia oryzae) is a major pest across much of South and Southeast Asia. Genetic studies on host plant resistance indicate that a single major gene generally controls the character.

33

38

43

48

% Diseased leaf area 4. Recombinant inbred lines (105) derived from the cross San-huang-zhan 2/Lijiangxin-tun-heigu were evaluated for disease leaf area in the blast nursery (right panel). The lines were DNA fingerprinted using 30 NBS-LRR and defense response gene sequences. DNA profiles of the resistant and susceptible groups (20 group–1) were used to construct a dendrogram (left) to depict the genetic relationship of the lines. Two major clusters were formed that correspond to the resistant and susceptible groups. In contrast, no cluster was formed using DNA profiles derived from anonymous markers. IRRI, 2000.

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Table 5. Status of molecular tagging and mapping of gall midge resistance genes. IRRI, 2000. Gene Gm-1 Gm-2. gm-3 Gm-4 Gm-5 Gm-6 (t) Donor Samridhi Phalguna RP2068-18-3-5 Abhaya ARC 5984 Duokang #1 Mapping population RP 320-300/Kranti Phalguna/Karmana RP2068-18-3-5/MW 10 IR63429/Abhaya ARC 5984/Kranti Duokang # 1/Feng Ying Zhan Linked marker(s) OPN-15, OPK-07 RG329, RG476, RG214 OPU-01, OPQ-12, OPAL-09, OPAC-02, OPAD-09 OPP-02, OPM-12, OPP-09 RM 210, RM 223, RM 256 OPB-14, OPR-19, OPP-09, OPQ-05, OPE-01, RM 101 OPM-06, RG214, RG476 Tagged or mapped Tagged Mapped on chr 4 Tagged Mapped on chr 8 Mapped on chr 12 Mapped on chr 4

Molecular markers linked to the resistance genes are useful to facilitate the introgression of one or more of the genes into breeding materials. Efforts in the area of gene tagging, mapping, and pyramiding resulted in the tagging of six gall midge resistance genes (Gm-1, Gm-2, gm-3, Gm-4, Gm-5, and Gm-6t) with a number of RFLP, randomly amplified polymorphic DNA (RAPD), sequencetagged site (STS), and SSR markers. Four of the six known gall midge resistance genes have already been mapped on the rice genome (Table 5). Shortrange maps were established around the resistance loci in these mapping populations. The linked RAPD markers were cloned, sequenced from both the ends, and converted into more reliable and robust STS markers suitable for MAS. MAS kits were developed for use by breeders. The kits contain suitable STS primers for each marker and appropriate restriction enzymes to reveal polymorphism between the donor line and the recipient lines. These kits are in use in India and China to transfer different Gm genes into commercial cultivars, and for MAS-based pyramiding of gall midge resistance genes to achieve broader and more durable resistance. Genetic basis of inbreeding depression and heterosis in rice Z K. Li, L.J. Luo, H.W. Mei, D.L. Wang, Q.Y. Shu, R. Tabien, D.B. Zhong, C.S. Ying, J.W. Stansel, G.S. Khush, and A.H. Paterson The genetic basis of inbreeding depression and heterosis for grain yield and its components in rice were investigated in five related rice mapping populations using a complete RFLP linkage map of

182 markers, replicated phenotyping experiments, and the mixed model approach. The mapping populations included 254 F10 RILs derived from a cross between Lemont (japonica) and Teqing (indica), and two BC and two test-cross hybrid populations derived from crosses between the RILs and their parents plus two testers (Zhong 413 and IR64). Significant inbreeding depression in the RI population and a high level of heterosis in the BC and test-cross hybrid populations were observed for all traits except grain weight. The mean performance of the BC or test-cross hybrids was largely determined by their heterosis measurements. A large number of epistatic QTL pairs and a few main-effect QTLs were identified and found to be responsible for more than 65% of the phenotypic variation of the traits. Three conclusions concerning the QTLs associated with inbreeding depression and heterosis in rice were reached. q Most QTLs associated with inbreeding depression and heterosis in rice appeared to be involved in epistasis. q Most (~90%) QTLs contributing to heterosis appeared to be overdominant. q For most traits, QTLs showing additive gene actions and those of nonadditive gene actions appear to belong to different groups of genes and few loci show both additive and nonadditive (partial or complete dominance) gene actions. These observations tend to implicate epistasis and overdominance, rather than dominance as the major genetic basis of heterosis in rice.

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International rice molecular breeding program for massive introgression of desirable QTLs into elite genetic backgrounds Z.K. Li, S.B. Yu, W.J. Xu, J. Ali, C.H.M. Vijayakumar, J. Domingo, R. Maghirang, C. Aquino, and G.S. Khush The International Rice Molecular Breeding Program genotyped 203 parental lines with more than 150 anchor SSR markers, revealing the genetic diversity of the gene pools and its geographic pattern. A high level of overall genetic diversity of 0.69 and an average of 6.2 alleles per SSR locus were revealed, indicating a diverse genetic basis of the gene pools. Prevalent alleles with frequencies >50% were observed at 34 of the SSR loci across the rice genome. Markers on chromosomes 5 and 6 showed the maximum japonica-indica differentiation. Cluster analysis of the 203 parents revealed four major cultivar groups and eight subgroups (Fig. 5). Group I corresponded to the classical indica group, while group IV to the classical japonica group. Groups II and III each represented a small portion of the sample and included some modern cultivars presumably derived from indica and japonica crosses. The among-group variation accounted for only 8.6% of the total genetic diversity, while variation subgroups within groups accounted for 15.2%, and within-subgroup variation accounted for 76.2% of the total variation. The indica group (I) showed the highest level of diversity at all levels. In particular, indica lines from China and India were apparently differentiated from each other, forming two separated subgroups. Backcrossing and selection achieved a massive flow of desirable genes-QTLs from the 200 parental lines into five elite parents (IR64, NPT, two maintainer lines, and Teqing) to develop five NIL sets. More than 700 crosses between the 200 donor lines and the recurrent parents were made and advanced to BC2F2 and BC3F1 generations. A largescale phenotype screening for tolerances for drought, salinity, and many other agronomic traits was initiated in the 2000-01 DS.

Subgroup 1 (54) Subgroup 2 (5) Subgroup 3 (32) Subgroup 4 (46) Ba-Bao-Mi (Yunnan) Subgroup 5 (15) Subgroup 6 (11) Subgroup 7 (28) Subgroup 8 (9) Jalmagna (India)

I (indica)

II

(japonica)

III (Intermediate) IV (deepwater)

5. Classification of 203 Molecular Breeding Program (MBP) parental lines into four major cultivar groups and eight subgroups based on SSR markers. IRRI, 2000.

Identification of QTLs for disease resistance and important agronomic traits Z.K. Li, D.B. Zhong, J.L. Xu, S.B. Yu, A. Sanchez, L.J. Luo, W.J. Xu, J. Domingo, R. Maghirang, C. Aquino, and G.S. Khush
QTLS FOR LODGING RESISTANCE AND PLANT DEVELOPMENT TRAITS IN RICE

Lodging resistance is an important trait associated with high yield potential of small-grain crops. Three groups of traits related to lodging resistance were investigated to gain understanding of the genetic basis of lodging resistance and facilitate genetic improvement in rice. The first group of traits included basal-internode-related traits, such as culm wall thickness of basal first-elongated internode (CWT), diameter of basal first-elongated internode (DBFI), length of basal first-elongated internode (LBFI), and length of basal second-elongated internode (LBSI). The second group of traits included plant-heightrelated traits, i.e., length of upper first internode (LUFI), length of upper second internode (LUSI), length of upper third internode (LUTI), length of upper fourth internode (LUFI), panicle length (PL), and plant height (PH). The third group of traits was related to different development stage, which contained elongated internode number (EIN), non-elongated internode number (NEIN), total leaf number on the main stem (TLN), and heading date (HD).

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Table 6. Important main-effect QTLs affecting traits associated with basal internodes, plant height, and plant development detected in Lemont/Teqing RILs. IRRI, 2000. M-QTLs QCt1 QCt8 QDbfi2 QDbfi3b QDbfi4 QDbfi5 QDbf.i10b QLbi6a QLbi6b QLbsi1 QLufi7 QLufi8 QLufi9 QLusi2 QLusi3 QLusi6 QLusi11 QLusi12 Trait CT DBFI CT DBFI DBFI DBFI DBFI DBFI LBFI LBFI LBSI LUFI LUFI LUFI LUSI LUSI LUSI LUSI LUTI LUFOI PH LUFOI LUFOI LUFOI PH LUFOI PL PL PL PL PH PH HD NNEI NNEI NEI TLN HD NEI NEI Chr 1 8 2 3 4 5 10 6 6 1 7 8 9 2 3 6 11 12 Marker interval RZ801 – RZ14 OSR7 – RM230 RM154 – RM279 RM227 – RM85 G379 – Ph CDSR49 – RG346 RG752 – RG1094f RM30 – RM340 RM253 – C RM23 – RD1.5 RD7.10 – RD7.11 OSR7 – RM230 RM257 – RM242 RD2.8 – RM208 RM227 – RM85 C - G200a RM286 – RM20 RG20q – RG91q LOD 7.60 6.17 4.48 5.15 6.50 5.33 4.81 7.07 5.16 4.86 5.06 5.04 6.87 6.46 5.63 5.48 8.87 5.34 12.34 12.03 5.81 8.44 7.99 4.11 4.98 10.55 10.67 6.70 5.98 5.47 5.06 8.40 6.98 3.93 13.47 11.23 16.04 15.23 4.98 4.58 A 0.047 0.21 –0.032 –0.16 –0.22 0.15 –0.17 –0.23 –0.20 0.19 0.37 0.67 -0.76 0.90 –0.61 0.69 –0.72 –0.61 –0.92 –0.68 –2.37 –0.58 0.49 –0.42 –1.96 0.62 –0.68 –0.77 0.63 0.50 2.32 3.34 2.07 0.49 –1.02 –0.21 –1.18 –3.60 0.12 0.11 R2 9.5 6.9 4.6 4.0 7.4 3.6 4.6 7.9 7.0 6.4 5.2 4.2 5.3 7.5 4.9 6.2 6.8 4.9 10.9 10.3 5.1 7.5 5.3 3.9 3.5 8.7 9.2 11.6 7.8 4.9 4.8 10.0 6.5 3.3 14.2 14.2 19.6 19.8 4.8 3.6

QLuti6b Qlufoi1 Qlufoi3 Qlufoi4 QPl3 QPl5a QPl5b QPl9 QPh8 QPh10 QNnei1 QNnei3

6 1 3 4 3 5 5 9 8 10 1 3

G1314b – HHU37 R210 – RG811 C515 – RG348a RM252 – RM303 RM227 – RM85 R569a – RM249 RM249 – RG13 RZ698 – RM219 RM223 – RZ323a RM271 – RZ400 RM24 – RZ776 RG348a – C636x

QNei4 QNei11

4 11

RG190 – RG1094e RM120 – RM202

A total of 65 main-effect QTLs were identified and mapped to all 12 rice chromosomes (Table 6). The number of significant QTLs affecting each trait ranged from 3 to 7. The percentage of phenotypic variation explained by each QTL ranged from 5% to 34.3%. These QTLs and epistasis provided useful information for MAS for these traits.

QTLS FOR TRAITS ASSOCIATED WITH THE PRIMARY SINK SIZE AND GRAIN MILLING QUALITY IN RICE

The genetic mechanism underlying the relationship between three traits of the primary sink size (spikelet number panicle–1, panicle number plant–1, and grain weight) and their nine component traits

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was also dissected in the RILs. Forty-eight maineffect QTLs affecting these traits were identified and mapped to all 12 rice chromosomes. Those QTLs collectively explained more than 60% of the total variation of individual traits in the RILs. Most main-effect QTLs tended to affect more than one related trait, providing insights into the genetic basis of the trait correlation, and useful information for marker-aided improvement of both sink size and grain quality. Some main-effect QTLs with large effects, and detected with large LOD scores, provided good candidates for MAS to improve the sink size and grain quality. These included QPn4 for panicle number, QPbl4, QPbn3a, QPbn3b, and QPbn4 for panicle branching and length; QGl3, QGl5, QGl10, and QGv2 for grain length, or volume, or both; and QGs1 and QGs7 for grain shape and milling quality.
QTLS FOR QUANTITATIVE RESISTANCE TO BACTERIAL BLIGHT IN RICE

Races of BB interact with rice cultivars in a genefor-gene specific manner. The resistance of rice to Xanthomonas oryzae pv.oryzae (Xoo) has both qualitative and quantitative components. QTLs responsible for resistance to six Xoo strains, PXO611 (race 1), PXO85 (race 2), PXO79 (race 3), PXO71 (race 4), PXO112 (race 5), and PXO99 (race 6) were investigated using the same RILs. The major resistance gene (Xa4) contributed by Teqing allele and 20 main-effect QTLs were largely responsible for segregation of the resistance phenotype in the RI population. While most resistance QTLs appeared to be race-specific and had varied effects, two of them (QBbr5 and QBbr5) were effective against five and four Xoo races. Our results indicate that a high level of resistance against virulent Xoo races can be obtained by pyramiding multiple resistance QTLs. Anther culture S.K. Datta, L. Torrizo, G. Gregorio, S. Virmani, and G.S. Khush Anther culture of 50 F1 crosses was conducted to fix homozygosity and shorten the breeding cycle. These crosses were bred for irrigated lowlands, perennial upland rice, drought- and flood-prone low-

lands, and for Egyptian conditions. From crosses made in 1999, 461 DH lines were provided to the breeders for preliminary evaluation in the field and identification of promising lines. Anther-culture-derived lines were likewise used as parents in the breeding of varieties for floodprone environments (IR77675=IR71730-51-2/ IR61673-AC201) and wide hybridization (IR77409 to IR77423 utilized IR68703-AC24-1 as male parent). Other promising anther-culture-derived lines included q IR72132-AC6-1, which was entered as test material in the Salinity Tolerance Nursery of the National Rice Cooperative Testing Program and planted in the IRRI saline demonstration plot. q IR63352-AC202 (from the cross SR10255-B58-3-2/Untup), which was newly entered as a test material in the Cold Tolerance Nursery. q Lines selected for advanced field test evaluation for salinity tolerance—eight anther-culture lines from IR74099, one antherculture line from IR74104, and one antherculture line from IR74105. q Lines selected for advance field evaluation for salinity tolerance and blast resistance include 13 from IR74095, 11 from IR74096, 2 from IR74097, 2 from IR74098, and 1 from IR69992. q Line IR72976-AC1 (IR619133-49-1-3/ IR67962-84-2-2), which was selected as an NPT promising DH and grown in a demonstration plot in 2000 DS. Transformation K. Datta, J. Tu, N. Baisakh, L. Torrizo, E. Abrigo, N. Oliva, I. Ona, T.W. Mew, and S.K. Datta
ENHANCED RESISTANCE TO SHEATH BLIGHT FROM VARIOUS TRANSFORMATION METHODS

A binary plasmid vector containing a chitinase gene that confers resistance to sheath blight was constructed (Fig. 6) and used in the Agro-transformation of three rice varieties from different ecosystems: Basmati 122, a commercial aromatic variety; Tulsi, for rainfed lowland; and Vaidehi, for deepwater areas. T0 plants were analyzed using Southern blots to detect the integration of chitinase and hph genes. The T0 plants positive for the genes

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Hind III
NOS 3

Pst I hph
35S

Hind III
35S

Hind III chitinase

1.9 kb fragment of pmnus7-13a

1.53 kb fragment of pGL2 (CaMV -CHIII)

Eco RI Sac I Kpn I Bam HI Hind III Pst I
LB nick

RB nick

Bg III
Gm ori

Sac I
RB lacZ

Xho I
LB

Xho I Sma I

Partial map of pCGN 1589 Agrobacterium cloning vector

Ps I Ba HI
RB 35S

Pst I Hind III Pst I Sac I hph
NOS3 35S

SalI

Hind III
LB

chitnase

6. Partial diagram showing the construction of the binary vector pNO1. The HindIII/Pstl fragment of pmnus7-13a containing the hygromycin phosphotransferase (hph) gene and HindIII fragment of pGL2 (CaMV-ChiII) containing the chitinase gene were cloned into the binary vector pCGN1589. The resulting binary vector is pNO1 (not drawn to scale). IRRI, 2000.

ranged from 56 to 98%, depending on the variety. The 1.5-kb band corresponding to the chitinase gene was observed in the chi+ plants, while for hph gene, bands with two different molecular sizes were observed in some cases. All T0 plants positive for chitinase by Southern analysis also produced the chitinase protein as detected by Western analysis. Inheritance of the transgenes was observed in the T1 generation and the segregation pattern conformed to a 3:1 ratio. T1 progenies of two selected Southernpositive T0 lines had significantly lower infection levels than the controls based on bioassay by inoculation of the test plants with sheath blight fungus Rhizoctonia solani. Homozygosity was achieved in all the cultivars in the subsequent T2 generation. Other indica rice cultivars, such as IR72, IR64, IR68899B, and MH63, were transformed via the biolistic method and Chinsurah Boro II via protoplast-mediated transformation with RC7 gene that likewise confers resistance to sheath blight. Molecular analysis confirmed the integration of this

gene in most plants in all test varieties. Western blot analysis of the different plant parts of Chinsurah Boro II (Fig. 7) and T2 progenies of a selected IR72 transformed line (Fig. 8) showed high levels of the 35-kDa chitinase protein.
INCREASING THE EFFICIENCY OF RICE TRANSFORMATION

Agro-transformation was used to introduce a construct carrying multiple genes (gus reporter gene, hph selectable marker gene, and Xa21 gene for BB resistance) into the elite indica maintainer line IR68899B. Stable integration was confirmed for the three genes using PCR and gene-specific primers. Although further molecular analysis and bioassay are in progress, it is clear that we demonstrated the possibility of simultaneously introducing several agronomically desirable genes into rice. We have also demonstrated that anther culture expedites the development of homozygous

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CB873 sheath

CB890 sheath

CB892 sheath

A

CB873 leaf

CB890 leaf

66.0 46.0 30.0 30.0 14.3 7. Western blot analysis of different transgenic plants T0 of Chinsurah Boro II (CBII) after infection. Leaf and sheath samples were taken from three different transgenic plants (CB873, CB890, and CB892). In all cases, the sheath samples showed more protein expression than the leaf samples. The leaf of CB892 showed no protein expression. The control is taken from leaves of nontransgenic CBII (not infected). The marker is the protein size marker. IRRI, 2000. 35 kDa
D B F

CB892 leaf

C

E

MW (kDa)

Control

Marker

M 46.0 kDa 30.0 kDa 21.5 kDa

1

2

3

4

5

6

7

8

9 35 kDa

8. Western blot analysis of transgenic homozygous T2 progenies of IR72. The arrow marks the 35-kDA expected protein band of the introduced chitinase gene. M = molecular weight marker, Lane 1 = parental T1 plant, lane 2 = negative control, lanes 3–9 = homozygous progenies of transgenic IR72. IRRI, 2000.

9. Infection and colonization of IR72 by Serratia marcescens IRBG500 (A,C,E) light micrographs, and (B,D,F) transmission electron micrographs. (A) Transverse section of an infected root. Bacteria can be seen within cortical cells and intercellular spaces (arrows). (B) Transmission electron micrograph of bacteria colonizing an intercellular space in the root cortex. (C) Longitudinal section of an infected stem showing intercellular and intracellular colonization. (D) Transmission electron micrograph of a stem protoxylem vessel containing numerous bacteria. (E) Transverse section of a leaf showing bacterial colonization in aerenchyma and intercellular space. (F) Transmission electron micrograph of microcolonies of bacteria attached to the cell wall in leaf aerenchyma. The bacteria were immunogold-labeled using a primary antibody raised against S. marcescens IRBG500 and a secondary goat anti-rabbit antibody conjugated to 15 nm gold particles. IRRI, 2000.

transgenic rice plants. Biolistic transformation of the popular variety Swarna with a vector carrying chitinase and hph genes was followed by anther culture of the T0 confirmed transgenic plants. Progenies of five selected primary transgenics were anther-cultured and gave 31 green plants. Twenty and eight showed both hph expression and integration of chi gene, anther-culture-derived plants were analyzed, confirming the stable integration of the transgenes. The banding patterns of the anther-culture lines were the same as the T0 parental lines. Employment of this novel strategy can reduce the duration of production of homozygous transgenic plants by almost half.

Biological nitrogen fixation P.M. Reddy, J.K. Ladha, P. Gyaneshwar, N. Mathan, R.B. So, R.J. Hernandez-Oane, V.S. Sreevidya, E.K. James, and B. Reinhold-Hurek A major goal of biological N2 fixation (BNF) research is to extend N2-fixing capacity to cereal plants such as rice. The strategies for rice include the establishment of effective endophytic associations and the development of legumelike nodulation.

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IRRI program report for 2000

COLONIZATION OF RICE BY DIAZOTROPHIC ENDOPHYTES

Endophytic strains of Herbaspirillum seropedicae Z67 and Serratia marcescens IRBG500 were marked with the gusA reporter gene and inoculated onto IR72 seedlings. Their colonization was studied under gnotobiotic conditions with different amendments to the assay medium. The endophytic colonization was monitored via bacterial enumeration and histochemical visualization of GUS expression of bacteria in plant tissues. As in legume-rhizobial symbiosis and plant-pathogen interactions, nutrient status, particularly NH4+ and Ca2+ concentrations in the surrounding medium, played an important role in the regulation of endophytic infection and colonization processes in rice. Novel diazotrophic isolates S. marcescens and H. seropedicae have an ability to colonize rice extensively without apparently causing any adverse effects on growth of the plants. These endophytes infect rice through roots and systemically spread to all parts of the plants, predominantly colonizing intercellular spaces, aerenchyma, and xylem tissues (Fig. 9). Experiments with inoculation of S. marcescens IRBG500 under gnotobiotic as well as greenhouse conditions showed a significant increase in root length and dry weight. There was, however, no significant difference in the total N of the inoculated plants compared with non-inoculated seedlings. Total N was typically 0.2–0.3 mg plant–1. Thus it appears that growth promotion in rice upon inoculation with S. marcescens was probably due to mechanisms other than N2 fixation. Our earlier studies showed that associative N2 fixation by diazotrophs in rice could be limited by the lack of carbon availability. Rice varieties tolerant of Al toxicity are known to release high amounts of organic acids in the rhizosphere to chelate Al. These organic acids can be a good source of carbon for diazotrophs in the rhizosphere. When inoculated with an endophytic strain of N2-fixing bacterium H. seropedicae Z67, Al-tolerant rice varieties (Moroberekan, IRAT104, and Azucena) showed significantly higher acetylene-reducing activity (ARA) compared with the semitolerant (IR43) and sensitive (IR45) varieties, with the latter showing ARA only when 5 mM malate was supplied externally. In further investiga-

tions, the representative Moroberekan incorporated significantly higher 15N2 than IR45. In addition, inoculation resulted in enhanced dry weight, total N, and total C content only in the Al-tolerant varieties. In spite of harboring similar numbers of bacteria as the Al-tolerant varieties, Al-sensitive varieties showed significantly lower N2 fixation, indicating that N2 fixation in Al-sensitive rice varieties could be limited by the inadequate availability of C to the associated diazotrophs.
GENETIC PREDISPOSITION OF RICE FOR FORMING SYMBIOSIS WITH RHIZOBIA

For rhizobia to infect the legume root, the bacterial nod genes must be induced by plant-produced flavonoids. Our studies indicate that the roots of specific rice cultivars, such as IR20, exude compounds that are able to induce the transcription of the nod genes of Rhizobium sp. NGR234 and Bradyrhizobium japonicum USDA110. These results suggest that rice roots, similar to legume roots, exude activators of rhizobial nod gene expression. Studies are under way to characterize the nod geneactivating compounds from rice root exudates. ENOD40 was proposed as playing a crucial role in initiation of nodule development in legumes. Transgenic rice harboring Pr35S-MtENOD40 was developed to assess its activity in promoting developmental changes in rice roots. Expression of Pr35S-MtENOD40 in roots led to extensive accumulation of amyloplasts in cortical cells. That sometimes promoted the development of hypertrophies from lateral root primordia and provoked the proliferation of cortical cells, albeit in an unrestricted manner, in the meristematic zone. These findings suggest that at least some of the cellular manifestations due to the activity of MtENOD40 appear to be similar in alfalfa and rice.

Exploiting biodiversity for sustainable pest management
Among the most important problems in rice pest management is the evolution of pest strains able to overcome genetic resistance factors in rice cultivars and the negative effects of pesticides on nontarget organisms in the environment. This project explores approaches to the use of biodiversity to improve the sustainability and environmental safety of pest man-

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Table 7. Benefit-cost ratio for 104 farmers in a mixture-planting project in Yunnan Province, China, 1997-2003. Benefit-cost ratio Discount rate (%) 1997-2000 15 50 100 2.7 2.0 1.3 1997-2007 22.0 8.7 7.8

The investment was recovered in 3 years following the beginning of the project in 1997 (Table 7). At a 15% discount rate, the benefit-cost ratio is 2.7 for the period 1997-2000. For 19972007, mixture planting will yield a benefit-cost ratio of 22. Even at 100% rate of discount, the benefit-cost ratio will still be high at 7.8, which means that the actual rate of return on investment is more than 100%. Durability of the Xa7 gene for bacterial blight resistance C.M. Vera Cruz, Jianfa Bai, J.E. Leach, S. H. Choi, R.J. Nelson, I. Oña, T.W. Mew, and H. Leung Plant resistance is the most effective strategy to manage BB caused by Xoo. Although single-gene resistance may not last long due to the rapid changes in pathogen populations, the Xa7 resistance gene has been found to provide durable resistance. We tested the hypothesis that the durability of Xa7 may be due to pathogenic fitness (aggressiveness and persistence) associated with Xoo virulence to rice lines with this resistance gene. We identified strains of Xoo race 9 haplotypes C-01 and C-05 that fell into four groups, (races 9a, 9b, 9c, and 9d), based on q lengths of lesions they caused on IRBB7, a near-isogenic line with the Xa7 gene; q the presence or absence of restrictionmodification system; and q presence or absence of a 4.2-kb BamHI fragment that corresponds to avrXa7. To characterize the molecular changes leading to virulence on IRBB7, the 4.2-kb BamHI fragment from a race 9b strain (PXO0314), a race 9c strain (PXO2684), and a wild-type race 3 strain (PXO1865) were cloned and sequenced. Domainswapping experiments between the mutant and the wild type genes were performed to determine the location of the relevant mutations leading to loss of avirulence function. Results indicated that the mutation in the genes from both PXO0314 and PXO2684 were at the 3′ terminus of the mutant avrXa7 genes. Two recombinant plasmids containing fragments from PXO2684 (pB2684 and pB1884) showed water-soaked lesions on IRBB7 (the mutant phenotype) indicating that the mutation was contained in the HincII-BamHI fragment in the 3′ terminus (Fig. 10). Sequence analysis of the en-

agement. The scope of the project extends from landscape ecology to microbial molecular biology. Impact on farmer income of varietal mixture planting I.M. Revilla, J.X. Fan, Y.Y. Zhu, Z.S. Li, T.W. Mew, and M. Hossain We assessed the impact of rice mixture planting for blast management in Yunnan Province, China, on pest management and farmers’ income. The rate of return to investment was calculated. One hundred and four farmer-adopters of mixture planting in four villages and 30 nonadopters in three villages of Shiping and Jianshui counties, Hong He prefecture, were interviewed in Jul 2000 to collect information on household characteristics, farm management practices, input use, yield, costs, and income. Data were analyzed using before-andafter and with-and-without comparisons to determine the impact of mixture planting. Mixture planting brought several environmental and economic benefits to the Yunnan Province farmers, where per capita income is low, farms are small, and rice contributes a high share to total farm income. Large-scale field trials conducted from 1998 to 1999 showed that blast severity was 94% less when one row of glutinous rice (Huangkenuo and Zinuo) was interplanted with four to six rows of hybrid rice varieties (Shanyou 63 or Shanyou 22). Adopters of mixture planting reported that the yield of the glutinous rice was 34% higher in 1999 than in 1996. That yield is about 84% higher than the average yield obtained by nonadopters in 1999. Mixture planting reduced pesticide expense by 44% for adopters because of decreased incidence of blast. The net returns above cash costs obtained by adopters in 1999 were $162 ha-1 higher than in 1996 and $320 more than those of the nonadopters.

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Xoo strain
PXO1865 PXO2684 PXO0314 PXO99A BP pB1865 pB2684 pB0314 pB1884

Relevant genotype Race 3 (avrXa7+) Race 9c (avrXa7 ) Race 9b (avrXa7
+/– –

Phenotype on IRBB7 HR 1WS

)

WWS WS

Race 6 (avrXa7) S H S B

HR WS HR

WS

pB2665 1 kb WT PXO1865 or PXO0314 MT PXO2684 nt aa nt aa

HR

GAA TTC GAA GCC CGC TAC GGA E F E A R Y E GAA CTC GAA GCC CGC GGT GGA E L E A R G E PXO1865 sequences PXO2684 sequences PXO0314 sequences

Vector Direct repeats Promoter

10. Location of mutated regions of avrXa7 alleles from the field isolates of Xoo. Phenotypes on IRBB7 were determined by infiltration of IRBB7 (Xa7) with Xoo wild-type strain PXO1865, and mutants PXOO314, PXO2684, and PXO99A containing plasmids with the cloned 4.2 kb BamHI fragments from PXO1865, PXO2684, and PXO0314 or their derivatives with swapped regions. The nucleotide and amino acid sequence alignment shows four nucleotide changes detected in pB2684 as compared with wild-type pB1865. These mutations that resulted in two amino acid changes alter AVRXa7 function in pB2684. Phenotypes at infiltration sites: IWS = intermediate, WWS = weak, and WS = strong water soaking. IRRI, 2000.

tire mutant allele from PXO2684 showed only four nucleotide changes (corresponding to two amino acid changes) from the wild-type avrXa7 gene. These results indicate that mutations associated with the 3’ terminus of the avrXa7 allele caused the loss of avirulence and aggressiveness functions in race 9c field strains. Plasmids with the wild-type (pB1865) and mutant (pB2684) avrXa7 fragments were used in studies with an Xoo strain (KL7M) mutated at the avrXa7 locus to confirm that the avrXa7 allele in race 9c strain PXO2684 had lost avirulence and aggressiveness functions. Infiltration studies of these strains revealed that the strain carrying the wild-

type plasmid [KL7M(pB1865)] and the wild-type strain PXO1865 elicited a hypersensitive response on IRBB7, while race 9c strain PXO2684 conferred intermediate phenotype and control KL7M(pHM1) conferred weak water-soaked phenotype. On IR24, KL7M(pHM1) and KL7M(pB2684) produced weak susceptible responses while KL7M(pB1865) and PXO1865 produced strong susceptible responses. These data support the conclusion that the mutations in the avrXa7 allele in the mutant pB2684 were responsible for the loss of both avirulence and aggressiveness functions in the field strains.

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Based on these results and those of complementary field studies, we propose that assessing the fitness attributed to avirulence gene mutations makes it possible to rank the relative durability of resistance genes.

Rice: a way of life for the next generation of farmers
Assessment of milled rice quality in the Philippine retail market R. Bakker, D. de Padua, R. Billate, C. Jawili, E. Jarcia, I. Barredo, and C. Mangaoang Asian rice farmers have dramatically increased yields through the adoption of high-yielding varieties. At the same time, Asian consumers have increasingly become more discriminating in terms of rice quality. IRRI agricultural engineers observed during a 1998 study that quality of most of the milled rice in selected markets in Manila and Laguna, Philippines, was substandard in terms of head rice and amount of discolored grains. A nationwide study of rice quality in the Philippine retail market was launched in 2000. The study evaluated milled rice quality characteristics such as % head rice, broken rice, brewer’s rice, discolored grains, chalky or immature grains, non-grain impurities, and amylose content. The study also included an assessment of the Philippine Grains Standardization Program. A total of 454 rice samples were taken from 279 representative retailers in 17 provinces during 2000 DS and WS. The retailers were asked about sales volumes, pricing practices, and consumer preferences. Distribution of monthly sales volume classified by grade indicated that 57% of rice in the retail market is sold as grades 1, 2, or 3, with 14% sold as premium rice. This indicates that rice grading has a place in the Philippine retail market because the major part of rice is sold with a grade indicated. However, based on quality analysis, we determined that 67% of rice in the retail outlets does not meet the standards for the lowest grade. Only 33% complies with either grades 1, 2, or 3, and that no rice complies with the premium classification. Key areas for quality improvement are the milling fractions (head rice, broken rice, brewers) and

damaged grains (chalkiness, insect damage, and heat and moisture damage). The primary factors that retailers consider in pricing, besides purchase cost, are whiteness of grain (46% of respondents) and whole grains or head rice (37%). Consumers select rice primarily based on whiteness and price, with volume expansion and taste as important secondary characteristics. Incorporation of cooking and eating qualities into the present standards would make the present system more relevant to rice consumers in the Philippines.

Socioeconomic studies for technology impact, gender, and policy analysis
This research generates information to support planning and prioritization of rice research and to improve the understanding of the interface between the diffusion of new technology, socioeconomic equity (including the gender dimension), and alleviation of poverty. Recent changes in Thailand’s rural economy: insights from a repeat survey of six villages M. Hossain and S. Isvilanonda Gross domestic product for Thailand grew at a rate of 8.5% y–1 during 1970-95, which, coupled with an equally impressive reduction in population growth, transformed Thailand from a low- to middle-income country and from an agrarian to an industrial economy. Thailand’s population of about 60 million in 2000 remains predominantly rural. We investigated developments in the Thai rural household economy by generating data from six villages representing different agro-ecosystems. A benchmark survey in 1987 obtained data on the impact of modern rice technologies on favorable and unfavorable production environments. A repeat survey was conducted in 1998. Suphan Buri Province in the Central Plain was chosen to represent the commercial rice production area, and Khon Kaen Province in the northeast region was chosen to represent the traditional rice production area. In Suphan Buri, the village of Wang Yang (SB1) represented the irrigated environmnent; Sa Ka Chome (SB2), the rainfed environment; and Jora Khae Yai (SB3), the flood-prone environment. In Khon Kaen, the village of Ban Koak (KK1) represented the irrigated environment; Ban Kaina

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(KK2), the rainfed environment; and Ban Meng (KK3), the drought-prone environment. The number of households surveyed was 273 in 1998 and 295 in 1987.
CHANGES IN RESOURCE BASE AND TECHNOLOGY FOR AGRICULTURE

seeding replaced transplanting as the method of crop establishment, and land preparation, threshing, and harvesting were completely mechanized. As a result, labor use declined from 44 to 10 d ha–1 in the Central Plains, and from 72 to 40 d ha–1 in the northeast.
STRUCTURE AND GROWTH OF HOUSEHOLD INCOMES

The average number of members per household declined substantially from 6.4 in 1987 to 5.0 in 1998. The decline was in all villages. The number of working members did not decline correspondingly but the proportion of children declined dramatically, indicating that population control in Thailand reached rural areas. The quality of the rural labor force, however, remains poor. The average schooling for the head of the household was only 3.5 years in 1987; it improved to only 4 years in 1998. The 1987 survey found that 9% of household heads had no formal schooling, and 85% attended only primary schools. That remained largely the same in 1998. The average age of rice farming household head was 53 years in 1987 and increased to 58 years in 1998, reflecting that farming is an occupation of older family members. The younger generation looks to move to more remunerative industrial and service sector occupations. Patterns of change in the size of landholdings differed between the two regions. There was further accumulation of holdings on the Central Plains as indicated by an increase in farm size from 5.1 ha in 1987 to 6.4 ha in 1998. Farm size declined in the northeast from 2.0 ha to 1.4 ha. The findings may be a reflection of higher rate of rural-urban migration from the Central Plains and the change in proportion of households receiving remittances from relatives living outside the village. In the Central Plains, households receiving remittances increased from 11 to 30% during 1987-98, compared with a marginal change from 20 to 24% for the villages in the northeast. Landlessness in 1987 was 8.3% for the Central Plains and 6.7% for the northeast, but it disappeared altogether by 1998. Employment opportunities in cities apparently induced the landless to migrate to urban areas and rice farming was increasingly done with family workers and farm machinery. There were dramatic changes in the adoption of labor-saving crop management practices. Direct

Farming was not the only source of income for the rural households. Nearly 24% of households reported nonfarm activities as the primary occupation of the family workers. If secondary occupations are considered, 38% of the household workers were engaged in nonfarm activities. The major nonfarm activities were industrial labor, construction labor, services and trade, and business. The average household income for 1998 was estimated at $3,213 and the per capita income at $645. Agriculture accounted for 61% of income. Rice cultivation accounted for only 27% of household incomes in 1998, a substantial decline from 45% during 1987. Per capita income grew by 6% y–1 during 198798 but a substantial portion of that growth was due to smaller household size. Household income grew at 3.9% y –1. The income from nonagricultural sources grew at a faster rate (4.9%) than that from agricultural incomes (3.2%). The fastest growing income source was nonrice agricultural activities— upland crops, horticulture, orchards, livestock, and fisheries. Although the area in rice-rice cropping and the adoption of modern varieties expanded, the income from rice cultivation declined in absolute terms.
CONCENTRATION OF INCOME AND SOURCES OF INCOME INEQUALITY

The degree of inequality in the distribution of income and its changes during 1987-98 can be seen in Tables 8–9. The income distribution appears highly skewed and inequality has grown over time. In 1998, the bottom 40% of households had a share of only 6% of the income, while 44% of income accrued to the top 10% of households. The income share of the bottom 40% halved during the 1987-98 period, the shares of the middle 50% remained almost the same, and the share of the top 10% in-

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Table 8. Changes in the distribution of per capita incomes by ecosystem in Thailand. Based on village surveys in 1987 and 1998. Rank of household Bottom 40% Middle 40% Ninth decile Top 10% Gini ratio Irrigated villages 1987 12.0 38.0 20.4 29.6 0.462 1998 9.3 35.5 17.8 37.5 0.529 Rainfed villages 1987 14.3 35.2 15.6 35.0 0.448 1998 6.2 31.8 16.7 45.2 0.608 All villages 1987 11.9 33.1 19.4 35.6 0.492 1998 5.9 31.5 18.5 44.1 0.564

Table 9. Changes in the distribution of per capita incomes by region in Thailand. Based on village surveys in 1987 and 1998. Rank of household Bottom 40% Middle 40% Ninth decile Top 10% Gini ratio Central Plains 1987 12.8 38.4 19.0 29.9 0.453 1998 6.5 34.5 17.6 41.4 0.573 Northeast 1987 14.6 34.7 15.5 35.2 0.446 1998 7.9 35.3 18.7 38.2 0.539

creased by 8%. The value of the Gini concentration coefficient deteriorated from 0.49 in 1987 to 0.56 by 1998. Income distribution worsened more for the rainfed villages than for the irrigated villages, and more for the Central Plains than for the northeast. A Gini decomposition analysis was conducted to gain insight into the sources of growing income inequality. The findings are reported in Table 10. The concentration coefficients for different sources of income reported in the table are pseudo-Gini ratios that measure the concentration of income from the source when households are ranked in the scale of per capita incomes.

The most unequally distributed source of income is from nonrice agriculture. It seems that the economically better-off households invest in expanding the area of profitable crops, such as fruit trees, water chestnuts, vegetables, and soybean. The share of the income from that source grew from 21 to 35%, and the Gini concentration coefficient deteriorated from 0.43 to 0.67 during the 1987-98 period. The concentration coefficient of rice income also increased as the adoption of high-yielding varieties expanded in the irrigated and flood-prone areas in the Central Plains villages where farm size is larger and farmers are better off than in villages in the northeast. The contribution of rice farming to the inequality of total household incomes did not increase, however, due to a decline in the share of rice in total household incomes. In 1998, incomes from nonagricultural sources were relatively more equally distributed than incomes from agriculture. Remittances were the least unequally distributed source of income. The distribution of income from those sources has also improved over time. Because improvement of human capital is the base for these sources of income, the

Table 10. Sources of income inequalities (Gini decomposition analysis) villages in Central Plain and northeast region in Thailand. Based on intensive surveys in 1987 and 1998. 1987 Sources of income Share of income (%) Concentration coefficient Contribution to concentration coefficient of total income 0.259 0.170 0.089 0.177 0.164 0.013 0.436 Share of income (%) 1998 Concentration coefficient Contribution to concentration coefficient of total income 0.392 0.161 0.232 0.170 0.157 0.013 0.562

Agriculture Rice farming Other agriculture Non-agriculture Nonfarm activities Remittances Total income

65.7 45.1 20.5 34.3 31.6 2.7 100.0

0.395 0.377 0.434 0.515 0.520 0.465 0.436

61.2 26.8 34.5 38.8 34.3 4.5 100.0

0.640 0.600 0.671 0.439 0.459 0.285 0.562

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findings suggest that investment in education would be a key factor to improve rural income in Thailand. Livelihood and income distribution in favorable and unfavorable rice ecosystems in Bihar, India M. Hossain, J. Thakur, and M.L. Bose Bihar, the poorest state in India, had a per capita net domestic product for 1995-96 estimated at $100 compared with $274 for India as a whole. The Indian Planning Commission estimated that 55% of Bihar’s population lived below the poverty line in 1993-94, compared with 36% in all India. Bihar, with 5.4 million ha of rice land, is India’s second largest rice-growing state, but rice yields are low at 2.1 t ha–1. Two-thirds of the rice area depends on rainfall, with frequent droughts and floods affecting rice production. High-yielding modern rice varieties and improved crop management, introduced following development of a reliable irrigation infrastructure, generated a respectable growth in rice production and productivity in the 1990s. The Rajendra Agricultural University (RAU), Pusa, Bihar, initiated a study in collaboration with IRRI to assess the extent of adoption of modern rice varieties in favorable and unfavorable ecosystems and to determine their impact on people’s livelihood. Surveys of 847 households in eight villages represented four different rice ecosystems (upland, rainfed lowland, flood-prone, and irrigated) and the state of development of infrastructure. The sample villages were classified according to the coverage of modern varieties and access to infrastructure. Villages with high coverage (more than 50% of rice area) of modern varieties were termed technologically developed, and those with low coverage as technologically less developed. The technologically developed villages had access to reliable irrigation (pumps and tubewells in contrast to canals) and better access to roads, markets, and electricity.
ASSET BASE AND LIVELIHOOD SYSTEM

46% of the households were marginal landowners with a holding of 1 ha or less. Thus land was not a significant means of livelihood for a substantial majority of the households. Nearly 31% of household heads had no formal schooling, and 17% attended only primary schools. Twenty percent of the household heads had attended college. Literacy level was high among the high caste, with 91% of the household heads having secondary or college-level education, and low among the scheduled caste and tribes, with 63% of the household heads with no formal schooling. Two-thirds of the households reported agriculture as the major source of livelihood; 9% reported agricultural wage labor as the principal occupation. The major nonagricultural occupations were rural industry (10%), services (12%), and trade and business (10%). The importance of nonagricultural occupations was higher among the scheduled caste and tribes (48%) than in the middle caste (29%). The importance of trade and services as major occupations was relatively high among the high caste and the better educated. Rice was grown on 53% of the land. Other crops grown were wheat (24%), vegetables (5.1%), pulses (5%), potato (4%), oilseeds (2.6%), and maize (2.6%). Modern varieties covered 69% of the rice area for the entire sample. Modern variety coverage was 100% in the irrigated ecosystem, 81% in the upland ecosystem, 37% in the rainfed lowland ecosystem, and 47% in the deepwater ecosystem, where modern varieties were grown with irrigation during DS. Rice yield was highest in the irrigated ecosystem (3.9 t ha–1) and lowest in the rainfed lowland ecosystem (1.5 t ha–1), with an overall average 2.5 t ha–1. Irrigation was the key factor in determining the adoption of modern varieties and their yield.
STRUCTURE AND DETERMINANTS OF HOUSEHOLD INCOME

An average household owned 0.78 ha but operated 0.89 ha, indicating some absentee land ownership. Land ownership was fairly unequally distributed. Nearly 26% of households were landless. Another

The average annual income estimated for various economic activities was $1,350 household-1 and $206 person-1 for the entire sample. It was $262 person-1 for the technologically developed villages and $143 person-1 for the less developed villages, indicating a positive impact of the diffusion of modern agricultural technology and the development of infrastructure.

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Table 11. The structure of household income among 847 households classified as technologically developed or less developed in eight villages representing four different rice ecosystems in Bihar, India, 1996-97. Rajendra Agricultural University and IRRI, 2000. Households Av income ($) Share of earning from total the source Earner All house- household (%) households holds incomes 643 221 428 343 1047 1105 899 600 169 365 66 735 480 113 44.9 12.7 27.3 4.9 55.1 36.0 8.5

Source of income

the two types of villages, however, accounting for about 10% of income in less developed villages and 2% of income for the developed villages. Workers tend to withdraw labor from agriculture as economic conditions improve. A regression equation was estimated in linear form to assess the contribution of different factors to household incomes.
INCM = f(LAND, TNC, WRKRm, WRKRf, CPTL, INFRA, EDCN, CASTEh, CASTEm, MV*IRG, MV*RFD)

Agriculture 93.3 Rice cultivation 76.5 Nonrice agriculture 85.3 Agricultural wage labor 19.4 Nonagriculture 70.3 Services 43.4 Trade and 12.5 business Nonagricultural labor 21.9 All households 100.0

649 1335

142 1335

10.6 100.0

Although 77% of the households earned incomes from rice, it accounted for only 13% of household income (Table 11)—16% in the technologically developed villages and only 6% in the less developed villages. More than half of household income originated from nonfarm activities, and that share was similar in both types of villages. The contribution of agricultural wage labor differed markedly between

where INCM = annual income of the household, (in rupees) LAND = the size of cultivated land by household (ha), TNC = % of holding rented, WRKRm = number of male earners in the family, WRKRf = number of female earners in the family, CPTL = value of nonland fixed assets owned by the household, INFRA = infrastructure development (1 for developed, 0 otherwise), EDCN = education level of household head (1 for secondary and above, 0 otherwise), CASTEh = caste dummy (1 for high caste, 0 otherwise), CASTEm = caste dummy (1 for middle caste, 0 otherwise), MV*IRG = % area of modern varieties grown under irrigated conditions, and MV*RFD = % area of modern varieties grown under rainfed lowland conditions.

Household level data give the following estimate for the income function:
INCM = –33351 + 14853 LAND –77 TNC +24683 WRKRm – 2786 (9.27) (15.63) (–2.59) (19.83) (–1.92) +2.00 CPTL+ 9695 EDCN+ 1991 CASTEh+5324 CASTEm +4966 (10.06) (5.13) (0.68) (2.39) (2.49) –649MV*RFD + 16066 INFRA R2= 0.62, n=847, F=121.8 (–0.19) (9.39) WRKRf MV*IRG

The figures within parentheses are t values of the estimated coefficients. The value of the regression coefficient on LAND indicates that 1 ha of land contributes on the margin $414 to household income (1US$ = 35.38 rupees). The adoption of modern varieties in irrigated areas contributes an additional $142 (coefficient of MV*IRG) to household incomes. However, when modern varieties are grown as rainfed lowland rice, the household does not get any additional benefit, as indicated by the value of the regression coefficient of MV*RFD.

A male worker earns on the margin $689 y–1, but the marginal returns from the female worker is negative, indicating that the household employs female labor beyond the point where the marginal productivity of labor is zero. Workers who are educated in secondary schools, or to a higher level, earn on the margin $277 more than the less educated worker. The value of the caste coefficients indicates that a middle-caste household earns on the margin $152 more than a schedule caste or tribe (the control), keeping all other factors constant. But the marginal

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Table 12. Contributions of factors of production to household incomes. Data from 847 households classified as technologically developed or less developed in eight villages representing four different rice ecosystems in Bihar, India, 1996-97. Rajendra Agricultural University and IRRI, 2000. Less developed villages Factor Mean value Land (ha) Workers (no.) Capital (rupees) R2 0.65 2.50 1342 Regression coefficient 13,902 (11.50) 8,984 (16.91) 2.20 (0.72) 0.72 Mean value 1.11 2.22 2817 Regression coefficient 17,502 (12.48) 15,042 (18.01) 2.40 (8.82) 0.83 Mean value 0.89 2.36 2096 Regression coefficient 17,542 (18.38) 10,914 (22.77) 2.71 (11.35) 0.78 Developed villages All villages

The regression equation was estimated by forcing the intercept to be zero. All coefficients, which show the marginal contribution of each factor, are statistically significant at less than 1% probability error.

Table 13. The pattern of distribution of per capita incomes and household incomes among 847 households classified as technologically developed or less developed in eight villages representing four different rice ecosystems in Bihar, India, 1996-97. Rajendra Agricultural University and IRRI, 2000. Share of per capita incomes (%) Rank of household in the scale of per capita incomes Less developed villages 14.3 41.9 18.1 25.7 0.40 Developed villages All villages Share of household incomes (%) Less developed villages 13.8 41.9 18.9 25.5 0.40 Developed villages All villages

Bottom 40% Middle 40% Ninth decile Top 10% Gini concentration ratio

21.6 41.6 15.6 21.3 0.29

16.4 42.2 16.6 24.7 0.37

20.6 41.4 16.5 21.4 0.30

16.4 41.5 17.6 24.6 0.37

earnings of a worker of the high caste is not significantly different from one from scheduled caste and tribes, given the same endowment of other factors of production. Households in villages with good access to infrastructure earn on average $459 more than households in villages lacking those facilities. This additional contribution of infrastructure is nearly 47% of the average household incomes of the less developed villages. The impact of technological development on the returns to land, labor, and capital was assessed by running separate regressions on household income for technologically developed and less developed villages with those factors of production as explanatory variables (Table 12). The results show that the marginal return to land is about 26% higher in the developed villages than in the less developed villages. The difference in the marginal returns to capital is about 9% and that for labor is about 67%. It

appears that it is the low-income households (who depend more on income from labor for their livelihood) who gain more from technological progress and development of infrastructure than the high-income households (who are better endowed with land and physical capital). Improvement in the human capital content of labor would further augment this favorable income distribution effect.
CONCENTRATION OF INCOME AND INCIDENCE OF POVERTY

Income distribution in the sample villages was fairly unequal (Table 13). The bottom 40% of the households in the per capita income scale got about 16% of total income, while about 25% of the income accrues to the top 10% of the households. The income distribution was less unequal for the technologically developed villages (Gini coefficient 0.29) than for the less developed villages (0.40).

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Table 14. Incidence of poverty at different levels of adoption of modern rice varieties among 847 households classified as technologically developed or less developed in eight villages representing four different rice ecosystems in Bihar, India, 199697. Rajendra Agricultural University and IRRI, 2000. Village-household group Head count index (%) 54.9 55.5 Poverty gap index (%) 29.4 25.2 Squared poverty gap index (%) 20.7 15.6

Nonfarm households Farm households with 50% area in modern varieties Farm households with ≥50% Technologically less developed villages Technologically developed villages All villages

food production systems, taking into account socioeconomic factors in biophysically defined ecoregions. The ecoregional project was included into IRRI’s research program in 1998 to institutionalize a commitment to natural resource management (NRM) and to contribute to the development of new concepts, approaches, and methodologies for NRM at a regional (sub-national) scale. Exploring scenarios of rice supply and demand within a country C.T. Hoanh, S.P. Kam, P.M. Bolink, S. de Vries, H.T. Lap, D.K. Son, and A. Rala Most existing rice supply and demand models are applied at the national level and are driven by economic factors such as price and market volumes. However, supply and demand are also determined by biophysical and socioeconomic factors that vary geographically within the country. Our study analyzed the balance between rice supply and demand at the sub-national level, taking into account biophysical constraints of the resource base as well as socioeconomic and policy considerations. From the analysis, we draw implications on the demands of rice production on the resources of a country like Vietnam, a major rice-exporting country. A rice supply and demand analysis (RSDA) model was developed and implemented within a raster-based geographic information system (GIS) environment. The rice supply component of the model takes into account potential and attainable yields, cultivated area under different cropping intensities, and availability of irrigation. Estimates of rice demand are made based on population and consumption rates. The balance between supply and demand is made by region-level comparison between supply and demand estimates, after taking into account postharvest losses and other uses of rice apart from direct human consumption.
GIS MODELING FOR RICE YIELD AND PRODUCTION ESTIMATION

50.2 65.7 34.3 50.2

16.1 33.4 10.0 21.4

8.7 21.6 5.1 13.2

Using the official Planning Commission poverty line for rural Bihar in 1993-94, adjustments were made to construct a poverty line for the years of the survey (1996-97). This poverty threshold income was applied to per capita income for each household to estimate different poverty indices. The headcount poverty index is 66% in technologically less-developed villages compared with 34% for the developed villages (Table 14). For households with more than half of their rice area covered by modern varieties, about 45% of the households were below the poverty line, compared with 56% for other households. Other measures of poverty that take into account the distribution of income among the poor and thus measure the intensity and severity of poverty, such as the poverty gap index and the squared poverty gap index, show a similar pattern. These comparisons suggest that technological progress and infrastructure development have a substantial positive effect on poverty alleviation.

Implementing ecoregional approaches to improve natural resource management in Asia
IRRI has, since 1995, had the task of convening the Ecoregional Initiative for the Humid and Subhumid Tropics and Subtropics. The focus of the ecoregional approach is conservation and management of natural resources to develop sustainable

We estimated rice supply under various agroecological conditions with a Rice Yield Estimation for Potential and Attainable Production (RYSTPAP) model. RYSTPAP is a simplified

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9 t ha–1

9 t ha–1

9 t ha–1 31 Dec 0 t ha–1

0 t ha–1

31 Dec

0 t ha–1

31 Dec

01 Jan Maximum potential yield Maximum waterlimited yield

01 Jan Maximum nutrientlimited yield

01 Jan

Sowing date for maximum potential yield

Sowing date for maximum water-limited yield

Sowing date for maximum water-limited yield

11. Highest potential, water-limited, and nutrient-limited yields of a single rice crop and corresponding optimal sowing date (selected from yields of 24 sowing dates with half-month intervals) in Vietnam. IRRI, 2000.

11 t ha–1

X Rice Non rice

=

>1,500 t

0 ha–1

0

Selected yield of single or double rice

Rice area

Rice production

12. Rice yield, area, and production in Vietnam. IRRI, 2000.

process model designed to use minimum data sets that are more readily available at regional levels. It simulates potential, water-limited and nutrientlimited yields, which when multiplied by cultivated area provides estimates of potential and attainable production. Figure 11 shows that the highest potential and nutrient-limited yields are obtained with winter sowing in the south and central parts, and with summer sowing in the north. Maximum water-limited yields are associated with summer sowing throughout the country, corresponding with the rainy sea-

son from May to October. The returns to investment for irrigation is highest in the Mekong River Delta not only in allowing dry season cropping but also through productivity gains and production increase of the WS crop by supplemental water supply. Figure 12 shows estimated riceyield, area, and production. Selection of single or double rice crop in each grid cell of 4 km2 is based on a benefit-cost analysis — i.e., by assuming that farmers select double rice cropping only if the net revenue from two crops is higher than from a single crop. The current physical and planted rice areas reported for

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> 5,000 inhabitants 0

> 1,500 t 0

-

> 1,000 t 0

=

> 1,000 t < –2,200 t

Population

Rice supply

Rice demand

Rice balance

13. Population, rice supply, rice demand, and rice balance for a 2010 scenario for Vietnam. IRRI, 2000.

each region are disaggregated to the rice cells of the raster map. Reduction factors due to insect pests and diseases and postharvest losses are adjusted to match the province-wise average simulated yield with the reported average yield. Rice demand and balance estimation. Rice demand for human consumption in each grid cell is estimated from population and per capita rice consumption. The average per capita rice consumption in each agroecological region was obtained from a sample survey of 1000 households. An additional 10% of the estimated human consumption is added to account for livestock and other uses. The balance between demand and supply is calculated after a reduction factor of 15% was applied to the estimated production to factor in postharvest losses. Scenario analysis. The RSDA system can also be used for exploring future scenarios of rice supply and demand. Figure 13 shows one such scenario

analysis for year 2010, using the following assumptions: q rice production is maintained at the current level; q urban population increases at 5% and rural population at –0.6% y–1, given a projected total population of more than 85 million; q per capita income increases of 100% for urban and 50% for rural population over the 200001 period; and q current rice demand elasticities of income. The map of rice balance indicates that food security will be highest in the Mekong Delta and lowest in some parts of the Red River Basin and the central part of Vietnam. Such mapped output helps identify areas of rice deficit and is useful for designing the rice distribution system in the country. Table 15 shows that with this scenario,

Table 15. Per capita rice supply, demand, and balance by region: example of a scenario for the future (2010) in Vietnam. IRRI, 2000. Population 2010 (no. of inhabitants) Demand (kg) Supply (kg) Balance (kg) Urban
a

Region

Rurala

Totalb

North Mountains and Midlands Red River Delta North Central Coast South Central Coast Central Highlands Northeast South Mekong River Delta Whole country
a

14,000,246 17,895,398 11,456,023 6,497,882 2,647,235 13,261,012 19,814,450 85,572,246

163 210 169 164 164 92 501 248

104 90 142 142 142 94 143 104

216 205 203 194 194 206 213 208

230 191 219 212 214 190 229 212

-67 +15 -50 -48 -50 -98 +272 +35

Human consumption only. bIncludes rice for livestock and other use.

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surplus production will decrease nationally by about 50% from present levels. The RSDA system can be used as a decision support tool for policymakers to explore implications of policy, development options, and resource allocations on the in-country balance between rice supply and demand. Optimizing land use in South and Southeast Asia: a comparison of four SysNet case studies C.T. Hoanh, R. Roetter, P.K. Aggarwal, Sujith Kumar S., I.A. Bakar, A. Tawang, F.P. Lansigan, S. Francisco, A.G. Laborte, and N.X. Lai Demand for food in Asia will continue to increase while resources available for food production are expected to decline. Effective planning is needed to meet future food requirements with less arable land, less water, and less labor with which to produce staple food. A research challenge is to develop science-based planning tools for exploring ways to optimize use of limited resource use under multiple land use objectives. The Systems Research Network for Ecoregional Land Use Planning in Support of Natural Resource Management in Tropical Asia (SysNet) was initiated in 1996 to develop methodologies and tools for improving land use planning at the sub-national level. Four case studies were set up to develop, evaluate, and test these tools and methodologies: q Haryana State (HS) in northern India has increasingly faced serious resource degradation problems, which are partly related to intensified agricultural production systems. Shortage of water occurs in the uplands while waterlogging and salinization are observed in the lowland area. q The Kedah-Perlis Region (KP) in northern Peninsular Malaysia is the major rice bowl, contributing to 40% of the national rice production. Labor shortage and rising production costs are the most serious constraints to agriculture. q Ilocos Norte (IN) is a province in northwestern Luzon, Philippines. Rice is the main wet season crop in the lowlands, while diversified cropping is practiced in the dry season. Major

environmental problems are soil erosion on sloping land and groundwater pollution in the lowlands. q Can Tho Province (CT) in the Mekong River Delta, Vietnam, has 83% of the total area under farming, of which 69% are under various rice cropping systems. Generating income and employment in the rural area is one main issue, while markets for agricultural products are still underdeveloped. SysNet developed a land use planning and analysis system (LUPAS), a decision support system for land use planning. It applies an interactive multiplegoal linear programming (IMGLP) method to deal with conflicting objectives of stakeholders. LUPAS includes analytical tools to deal with uncertainties about future land use objectives, available resources, and production technologies. The methodology can be used to explore land use options by identifying stakeholder-defined goals and their feasibility, considering different scenarios, and determining the associated resource allocation requirements. In exploring options, what-if questions may be asked — e.g., How would agricultural production be affected if different crops or techniques are introduced? What would be the effects of changes in resources, local demands, markets, prices, and national targets on regional development? LUPAS has three components: q land evaluation, including assessment of resource availability, land suitability, and yield estimation; q scenario construction based on policy views and development plans, and q land use optimization in the form of an IMGLP model.
SCENARIO CONSTRUCTION AND EVALUATION

Scenario construction entails q diagnosis of the current situation, q defining the system, q identifying the what-if questions to be answered, and q identifying the relevant issues to be addressed. Stakeholders participating in the SysNet case studies tend to focus on goal achievement, tradeoffs among objectives, and resource use.

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Table 16. Results of land use scenarios for four SysNet case studies. IRRI, 2000. Target regions Scenario Main objective Kedah-Perlis KP-1 KP-2 Ilocos Norte IN-1 IN-2 CT-1 Can Tho CT2 Maximizing rice production CT-3 Maximizing employment HS-1 Haryana State HS-2 HS-3 Minimizing pesticide impact indexa

MaxiMaxiMaxiMaxiMaximizing mizing mizing mizing mizing regional food regional rice regional income production income production income

MaxiMaximizing mizing regional cereal income production

Main achievementsb Food production (million t) 1.07 1.20 Regional income (billion)c 14.08 RM 0.86 RM Employment (labor-d) Pesticide residue index Resource use (%) Land area Labor
a

0.22 6.95 Ps

0.48

1.8

2.4

1.3

8.0

12.6

10.5

3.47 Ps 4,858 VND 3,746 VND 3,926 VND 37.8 Rs 26.6 Rs 20.9 Rs 64 53 77 91.3 20.9 7.7

97 42

86 44

87 19

41 12

100 22

100 18

100 27

94 41

94 40

96 27

Pesticide impact index (defined as PII = quantity (g ha-1) x toxicity index x persistence index x 100). bValues in bold and underlined are optimal for the associated objective. cRM = Malaysian ringgit, Ps = Philippine peso, VND = Vietnamese dong, Rs = Indian rupee.

The scenario analyses are done iteratively, incorporating greater complexity at each iteration based on insights gained from previous runs.
EXAMPLES OF SCENARIO RESULTS: TRADE-OFFS BETWEEN LAND USE OBJECTIVES

Table 16 shows the trade-offs between different land use objectives for all four case studies. Higher income achieved for the scenario of maximizing regional income is consistently at the expense of lower food production, indicating that food crops do not provide as much regional income as other land use types. Land resource use is lower for scenarios of maximizing food production, e.g., KP-2 and IN2, than for those of maximizing income, e.g., IN-1 and KP-1. The extent of land usage under the scenario of maximizing food production reflects how much land is suitable for food crops in the region. Without specifying demands of other products, the land unsuitable for food crops is not cultivated; therefore only 86% of the land area is used in scenario KP-2 and 41% of the land area is used in scenario IN-2. In scenarios IN-1 and IN-2, the resources are not fully used because of

geographical mismatch between demand and supply of these resources (e.g., land, water, and labor). Employment generation is a major issue in Haryana, Ilocos Norte, and is most serious in Can Tho. Even for the scenario CT-3 of maximizing employment, only 27% of the rural labor force can be used. This indicates a potential social problem in a region with dense rural population (3.7 laborers ha -1 of agricultural land) and low level of industrialization and urbanization. Moreover, scenario CT-3 gives the lowest income per laborday at 50,000 Vietnamese dong (VND) labor d–1, compared with 76,000 VND labor d–1 for scenario CT-1 and 71,600 VND labor d-1 for scenario CT-2. This indicates that maximizing employment may be at the expense of improving labor efficiency. Maximizing income and food production also has significant impacts on the environment. The trade-off between economic development, food security, and environmental protection is illustrated in the Haryana case by a high value of pesticide impact index for scenarios H-1 and H2, which are 11 and 3 times that for scenario H-3, respectively.

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EXPANDED SCENARIOS AND WHAT-IF QUESTIONS

Program outlook
Elements of the Cross Ecosystems Research Program were incorporated into the enlarged projects in the Medium-term Plan that start in 2001. The functional genomics project will be housed in the program for genetic resources conservation, evaluation, and gene discovery. It will provide the backbone for gene discovery that will derive germplasm improvement. Many of the tools and much of the germplasm required for functional genomics have been developed. We will continue to advance the collection of mutants, introgression and substitution lines, and expand the phenotypic analysis of these genetic resources. Efforts will be devoted to developing a reverse genetics system to assign sequences to mutant stocks. Collections of stress-response EST will be used in gene array analysis for tolerance against biotic and abiotic stresses. Bioinformatics efforts will focus on establishing linkage between genomic databases and phenotypic data. The component will be strengthened by addition of a bioinformatics specialist. The biotechnology project will merge with new projects. Biotechnology tools such as anther culture, molecular marker-aided selection, and genetic engineering will be used for developing improved germplasm for favorable and fragile environments. Through the ARBN, we will disseminate candidate genes and informatic tools resulting from functional genomics research to NARS. ARBN will organize a training course on microarray technologies and bioinformatics at the end of 2001 to familiarize NARS researchers with the use of gene array technologies and available genomic resources and data. Research on exploiting biodiversity for sustainable pest management will become part of resource management research under intensified rice-based systems as well as resource management for rainfed and upland ecosystems. Research on rice as a way of life for farmers, which focused on identifying and evaluating technology and delivery systems, will become part of facilitating rice research for impact. Work on socioeconomic studies for technology impact, gender, and policy analysis will become part of a new pro-

Multiple-goal scenarios with objectives of maximizing both income and food security were further analyzed. In the Kedah-Perlis case, if the maximum possible rice yield target of 1.2 t ha–1 is set, the regional income would only be 44% of that for scenario KP-1. On the other hand, if a target of 14.08 billion Malaysian ringgit is set for regional income, the optimal rice production would be the same as for scenario KP-2 because no other crops can be converted to rice without reducing income. In the Ilocos Norte case, a scenario whereby water is shared within each irrigation system increases income (23%) and also rice production (39%) significantly. In the Can Tho case, the situation of employment generation may worsen in 2010 with population increase and reduced land area for agriculture. Model outputs show that if all farmer groups can practice improved technology that is currently affordable only by rich farmers, maximum employment will be lower, at only 20% of rural labor force. In the Haryana case, the model shows that it is not possible to achieve the optimal income or cereal production without increasing the pesticide impact index. A common issue in all four case studies is the conflict between income generation and food security, indicating that under current price ratios of different agricultural products, maximizing food production and employment will not optimize income. A multiple-goal optimization and analysis is needed to find out the extent to which all objectives can be achieved simultaneously. Another common issue is the mismatch in distribution of resources (land, water, and labor) in space and time. Improved resource management, e.g., upgrading irrigation systems and reallocating labor force, can improve income generation or food production, or both. Each case study focuses on some specific issues. These vary from environmental issue in the Haryana case to policy issue in the Kedah-Perlis, resource management in the Ilocos Norte case and socioeconomic issues in the Can Tho case. The SysNet project provides the opportunity to carry out such a comparative study to deal with issues that are common as well as specific to the various cases.

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gram: Understanding rural livelihood systems for research prioritization and impact. Research on ecoregional approaches to improve natural resource management in Asia will continue to address ecoregional issues related to conservation and management of natural resources and develop sustainable food production systems.

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IRRI program report for 2000

Rice genetic resources: conservation, safe delivery, and use

CONSERVATION OF RICE AND BIOFERTILIZER GENETIC RESOURCES Germplasm and information exchange 102 Genebank management 102 Germplasm characterization 103 Data management 103 Conservation of biofertilizer germplasm 103 Biosystematic studies of wild rices 103 Dynamic systems of genetic conservation 104

102

DELIVERY OF GENETIC RESOURCES: THE INTERNATIONAL NETWORK FOR GENETIC EVALUATION OF RICE (INGER) 106 2000 INGER nurseries 106 Distribution of nurseries 106 Utilization of 1999 INGER entries 106 Data management 106 THE INTERNATIONAL RICE INFORMATION SYSTEM ICIS and IRIS development 107 Partnerships developed with NARS 107 SEED HEALTH TESTING SERVICES 108 Seed health testing 108 Partnerships with Philippine Plant Quarantine Service 107

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Rice genetic resources: conservation, safe delivery, and use

The Swiss Agency for Development and Cooperation (SDC)-funded project, Safeguarding and Preservation of the Biodiversity of the Rice Genepool, was completed during 2000. The project had an important impact on rice germplasm conservation in 22 countries. There was continued consolidation of International Network for Genetic Evaluation of Rice (INGER) activities within the overall operations of the Genetic Resources Center (GRC). INGER began distributing electronic field books to collaborators during the year. The books will facilitate recording of data from INGER nurseries. INGERIS, the data management system for INGER, was further developed as part of the overall initiative to develop the International Rice Information System (IRIS). More than 200,000 records were added to the database.

Conservation of rice and biofertilizer genetic resources
Germplasm and information exchange M.T. Jackson, B.R. Lu, G.C. Loresto, and S. Appa Rao IRRI received almost 700 samples of Oryza sativa and 84 samples of different wild species from the Lao PDR, Tanzania, Philippines, and Costa Rica during 2000. These genetic materials had been collected in previous years under the international collaborative SDC-funded project Safeguarding and Preservation of the Biodiversity of the Rice Genepool. The project, initiated in January 1994, terminated at the end of June 2000. More than 24,700 samples of cultivated rice and 2,400 samples of wild rice were collected in 165 missions from 22 countries in Asia, sub-Saharan Africa, and Costa Rica. More than 80% of the cultivated samples and almost 70% of the wild samples are now safely preserved in IRRI’s International Rice Genebank. Genebank management M.T. Jackson, F. de Guzman, R. Reaño, and S. Almazan Germplasm multiplication activities during the 2000 dry season (DS) included 4,583 newly acquired samples. In addition, 1,978 O. sativa accessions were rejuvenated. Field multiplication of the majority of samples was successful, but some of the newly acquired samples either produced only a small amount of seeds at IRRI, did not germinate, or were poorly adapted. Those samples will be entered in future regeneration cycles. About 130 O. glaberrima accessions were also successfully reju-

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venated. Seed stocks of about 1,000 wild species accessions and newly acquired samples were successfully increased during the 2000 DS and wet season (WS) in the nursery screenhouse. We added 4,716 accessions to the Base Collection, and 4,035 newly registered accessions were added to the genebank collection after initial multiplication. All germplasm samples were tested for germination and seed health prior to long-term conservation. We monitored the seed viability of about 8,000 accessions in the Active Collection as part of the routine management of the germplasm. An inventory of all germplasm in both the Active and Base Collections was done to ensure accuracy of information in the International Rice Genebank Collection Information System (IRGCIS). We distributed almost 7,000 seed samples in response requests from scientists from 24 countries. Of those samples, 1,661 were wild species—an increase in the number of requests for seeds of wild species over previous years. Germplasm characterization M.T. Jackson, R. Reaño, and S. Almazan We characterized 1,640 accessions of O. sativa for vegetative and reproductive traits in the field and 345 samples of wild species in the nursery screenhouse. The postharvest characterization of all 1998 WS panicle samples and 85% of 2,200 panicle samples from the 1999 WS were finished. We collected 136 samples of wild species for the herbarium during the 2000 WS and about 70 specimens from 1999 WS were added to the herbarium. Data management M.T. Jackson. A.P. Alcantara, and E.B. Guevarra The year 2000 was a busy one for database enhancement. We migrated the IRGCIS back end from Oracle 7.2 to version 8.0, and front end from Developer 2000 v.1.2 to v.1.5. This was not a straightforward upgrade but involved the recompilation and testing of many system modules over several months. IRGCIS is now on a dedicated server, purchased through the Systemwide Information Network for Genetic Resources (SINGER). Under the upgraded version of IRGCIS, multi-tasking is possible and has permitted even greater flexibility of data man-

agement resources. We are currently improving the design of the IRGCIS data entry modules to take advantage of the capabilities of the new environment. IRGCIS is fully accessible to all IRRI staff members through the institute’s local area network. The SINGER central database at CGNET Services in Palo Alto, California, was successfully updated with germplasm data of the entire collection from IRGCIS. As part of a CGIAR systemwide initiative and with funding from SINGER, we began a data-quality-control exercise for IRGCIS. By the end of 2000, we had verified passport and collecting mission data for 54,795 accessions (more than 50% of the registered accessions in the collection). The design and implementation of a new front end for IRGCIS on the worldwide web was a key data management activity. The front end was developed in SGRP tool kit. By year’s end, we had developed a first prototype and expect to have a beta version for wider testing and accessible internationally by mid-2001. A link to IRGCIS live passport data was established for the herbarium database to facilitate entry, retrieval, and storage of herbarium data. We responded to 47 requests for information from IRRI staff members and to 35 requests from outside IRRI. Conservation of biofertilizer germplasm J.K. Ladha and T.S. Ventura We supplied 18 Azolla, 12 N2-fixing bacteria, 33 Rhizobium, 12 blue-green algae, and 19 aquatic legume samples in response to 24 requests from 10 countries during the year. The collection remains at 1,333 accessions and there is continued long-term preservation of Azolla as shoot-tip and liquid cultures, blue-green algae on agar slants, and bacterial strains by lyophilization, agar slants, and storage at subzero temperatures. The Biofertilizer Information System (BIOFIS) is used routinely to update information about the collection and respond to requests for biofertilizer germplasm. Biosystematic studies of wild rices B.R. Lu, M.T. Jackson, A. Juliano, and M.E. Naredo We produced intraspecific nd interspecific hybrids from crosses involving O. nivara and O. rufipogon

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103

Table 1. Seed set of crosses and pollen stainability of hybrids from hybridization of O. nivara and O. rufipogon and O. meridionalis. IRRI, 2000. Cross Seed set (%) Pollen stainability (%)

Bases 400 350 300 250 200 150 100 50 Level 1 2 3 4 5 6 7 8 9 1011 12 13 14 15 16 17 18 19 20 2122

O. nivara – O. rufipogon O. nivara × O. nivara O. rufipogon × O. rufipogon O. nivara × O. rufipogon O. rufipogon × O. nivara O. meridionalisa NT × NT Q×Q NT × Q Q × NT

11.5 9.4 12.9 6.1 14.6 11.9 17.9 9.5

(0–27.6) (0–40.0) (0–55.9) (0–39.2) (0–41.7) (0–33.9) (0–39.0) (0–28.4)

84.6(52.1–96.9) 69.8 (2.2–98.3) 74.2 (0.4–98.7) 69.7 (6.7–94.2) 56.4 (1.3–96.1) 76.6 (0.9–98.9) 27.8 (1.6–61.6) 10.4 (0–51.1)

1. Microsatellite markers of parents (lanes 2–5 and 12–13) and F1s (lanes 6–11 and 14–21) of O. meridionalis generated by primer pair RM19. Hybrids exhibited the parental bands while the selfed plants (lanes 8,18, 20, and 21) showed a single band. Lanes 1 and 22 are sizes 50–400 bases. IRRI, 2000.

a NT = accessions from the Northern Territory, Q = accessions from Queensland.

and intraspecific hybrids for O. meridionalis from Northern Territory (NT) and Queensland (Q) in northern Australia to complete studies of the AAgenome wild species, the closest relatives of O. sativa (Table 1). Crossibility among the O. nivara and O. rufipogon accessions was generally low. Mean seed set ranged from 6.1% among the O. rufipogon × O. nivara crosses to 12.9% in the reciprocal cross. However, hybrid fertility indicated by mean pollen stainability was generally high, ranging from 69.7% in O. rufipogon/O. nivara hybrids, to 84.6% in the O. nivara intraspecific hybrids. Mean seed set in crosses among the O. meridionalis accessions ranged from 9.5% in Q × NT to 17.9% in NT × Q. The hybrids from these crosses showed variable fertility. Hybrids from accessions from the same general region were generally fertile, with a mean pollen stainability of 56.4% in NT × NT hybrids, and 76.6% in Q × Q hybrids. Mean pollen stainability was markedly lower, however, in NT × Q hybrids (27.8%) and Q × NT hybrids (10.4%), which suggested subspecific differentiation between the two regions, and corroborated data from morphological and RAPD analysis. The hybrid status of F1 plants was confirmed using microsatellite markers (Fig. 1). Dynamic systems of genetic conservation J.L. Pham, M. Calibo, M. Belen, and S. Quilloy We analyzed the genetic diversity of Safri and Sathka, two popular traditional rice varieties from the Bastar Plateau, Madhya Pradesh, India. The ge-

netic variation within each of the varieties was studied by analyzing the microsatellite polymorphism of 30 Safri samples collected from 10 villages in Raipur and Bastar and 24 Sathka samples from eight villages in Bastar. In both cases, considerable intravarietal variation was observed. This indicates that not all Safri or Sathka samples are identical, and several factors may have acted to produce this variation. Misnaming of varieties by farmers is one factor that could account for extreme differences. For both Sathka and Safri, one dominant genotype or cluster can be identified and serve as a reference cluster. The molecular characterization of the varietal group Sathka showed that samples originating from the same village tend to cluster (Fig. 2), suggesting they result from local processes of genetic differentiation. On-farm conservation in this area could therefore be dynamic conservation in terms of evolution. We explored potential strategies to promote onfarm diversity in Cagayan Valley, Philippines. The first approach was concerned with how to make diversity a viable option for farmers. Earlier results had identified late-maturing photoperiod-sensitive Wagwag varieties as endangered, as farmers tend to replace them with varieties whose duration permits double cropping. The idea of investigating new cropping patterns came from the observation of the practices of one farmer who was planting his traditional varieties in late October, a full 3 months after his neighbors. According to him, this practice posed no risk, and he felt he achieved higher yields than his neighbors with his traditional varieties.

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Chindawara Chindawara Chingpal Chingpal Kumli Chingpal Mardum Tangiajodi Kumli Kumli Kumli Mandhar Mandhar Kumli Lamni Lamni Lamni Lamni Tangiajodi Mandhar Mandhar Mandhar Kumli 0.13 0.35 0.56 0.78 1.00

Coefficient of similarity (Jaccard) 2. Cluster analysis of 25 accessions of traditional variety Sathka by village of origin (seven microsatellite primers, UPGMA). IRRI, 2000.

Field trials at IRRI confirmed these observations. Not only did late planting decrease the duration of the Wagwag varieties (Fig. 3), there was an increase in yield (Fig.4). From this, we proposed a new cropping pattern allowing farmers to double-crop with both modern and traditional varieties. This system needs wider testing. The second research direction is related to the strengthening of farmers’ access to diversity. We analyzed the impact of a 1998 seed distribution of traditional and modern varieties. In all, about 1.5 t of seed had been distributed, comprising 609 twokg bags of modern variety seeds and 105 one-kg bags of traditional variety seeds. It appears that the small amount of seeds given to each farmer had actually limited the efficiency of the distribution. Only 57% of the bags of modern varieties and 32% of the bags of traditional varieties were successfully multiplied. Nevertheless, the seed distribution modified the ongoing trend in Cagayan Valley of a decreasing number of farmers growing traditional varieties (175 farmers in 1996, 110 in 1997, and 84 in 1998), as the number increased to 148 in 1999. This seed distribution illustrates the need for genebanks to develop an expertise in the restoration of local diversity.

Days to heading 100

80
Wagwag IR64-IR66

60

40 0 0 29 Sep 10 20 30 29 Oct 40 9 Nov 50

Planting date 3. Effect of planting date on the heading date of Wagwag varieties. Mean values are shown because there was no significant difference among Wagwag and among IRRI varieties. IRRI, 2000.

The database of most of the genetic and socioeconomic data gathered during the 5-year project was consolidated and will be distributed to the project partners.

Rice genetic resources: conservation, safe delivery, and use

105

Grain yield (t ha–1) 10

8

6

4

2

Wagwag, Wagwag Pino Wagwag red, bilog Wagwag tawataw IR64-IR66 10 20 30 29 Oct 40 9 Nov 50

0

0 29 Sep

Four sets each of irrigated lowland (15 varieties), rainfed lowland (11 varieties), and upland (13 varieties) yield nurseries were prepared as part of the Australian Centre for International Agricultural Research-funded project: Seeds of Life—East Timor. A total of 1,053 breeding lines nominated for testing in 14 nurseries were multiplied during the 19992000 DS. Brazil, Cambodia, China, Malaysia, Myanmar, and the Philippines nominated 68 breeding lines and varieties to INGER in 2000. WARDA nominated 220 breeding lines, of which 92 originated from 22 NARS and the remainder from WARDA and other international centers. We also received 299 nominations of materials from the Plant Breeding, Genetics, and Biochemistry Division of IRRI. Utilization of 1999 INGER entries Two hundred and eighty-seven entries tested in the 1999 INGER trials were selected as parents in hybridization in 10 NARS (Table 2). These selections originated from the breeding programs of 27 countries. Thirteen NARS conducted follow-up yield trials where 519 breeding lines selected from the 1999 INGER nurseries were evaluated. Data management The development and testing of the INGER Information System (INGERIS) and its link to IRIS was
Table 2. Utilization of 1999 INGER entries by participating NARS. Entries (no.) Country Used in hybridization Bangladesh Cambodia China Egypt India Korea Myanmar Nepal Pakistan Philippines Thailand Turkey Vietnam Total 4 – 61 37 42 25 66 10 – 10 15 – 17 287 Tested in yield trials 18 42 30 37 72 3 123 35 61 9 57 12 20 519

Planting date

4. Effect of planting date on yield of Wagwag varieties. Mean values are shown for groups of varieties that significantly differ from each other. IRRI, 2000.

Delivery of genetic resources: The International Network for Genetic Evaluation of Rice (INGER)
2000 INGER nurseries E.L. Javier, C. Toledo, V. Lopez, and R. Reaño Three hundred and sixty-eight breeding lines from 35 NARS and 361 breeding lines from five international agricultural research centers (IRRI, IITA, CIAT, IRAT, and WARDA) were organized into seven ecosystem-oriented nurseries and three stressoriented nurseries. The stress-oriented nurseries were composed to screen for tolerance for problem soils and resistance to blast and tungro. Distribution of nurseries We distributed 281 nursery sets to 29 countries— about 90% of the sets to 20 countries in Asia and the remainder to Africa (Ethiopia, Mozambique, Senegal, and WARDA), Latin America (Bolivia, Brazil, Surinam, and Venezuela), and Italy. We processed and distributed 509 seed samples requested by rice scientists from 24 countries, IRRI, and WARDA.

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completed. A new seed inventory system was developed to avoid rearrangement of seeds in storage every year. The new system has location of seeds identified by a locator ID consisting of the cabinet number, shelf number within the cabinet, and seed container number within the shelf. Electronic field books for all nursery types were developed as data entry tools to IRIS and INGERIS. They were tested at sites in China conducting 2000 observational nursery trials. Nursery data submitted by cooperators for 1999 were encoded at IRRI using the electronic field books.

The International Rice Information System
The IRIS is fully functional for managing germplasm enhancement and evaluation data. Information on the genealogy of more than 900,000 lines is available. Integration of IRIS and INGERIS has progressed so that all genealogy information for INGER nominations enters through IRIS GMS, and evaluation data are captured into IRIS DMS via electronic field books. Almost 50% of historical INGER evaluation data have been transferred to IRIS. The use of IRIS was extended to IRRI’s hybrid and wide hybridization breeding. Furthermore, we added information on 200,000 breeding lines and more than 4,000 released varieties worldwide. Information on all IRRI’s recurrent selection populations and several international rice recurrent selection populations was added to IRIS. All genealogy and nomenclature data for the functional genomics mutant stocks have been loaded into IRIS, and we have demonstrated the ability of IRIS to manage phenotype data and links to sequence information. A prototype web interface was developed for functional genomics work using mutant stocks. IRIS was used in studies of the impact of rice breeding conducted by CGIAR centers, analysis of genetic flows to and from the Philippines, and for data mining on varietal response to soil stresses. ICIS and IRIS development C.G.McLaren Development of the Genealogy Management System (GMS) module of ICIS continued, and IRIS

DMS was populated with genotype data and genetic maps for three rice-mapping populations. This will form the foundation data for the CGIAR-NCGR collaboration on comparative mapping. ICIS data mining facilities and trait management tools were also developed. ICIS data structure modifications agreed at the ICIS 2000 workshop were implemented and accommodated in dynamic link libraries. The main new feature of GMS is an efficient method of documenting data corrections and automatically applying local corrections to central data records in real time. This means that genealogical analysis involving the corrected records reflects the corrections without first updating the central database. ICIS breeders’ tools were further developed to accommodate different breeding strategies and crops. These tools are now used in rice and wheat breeding projects and are available for other crops. Training materials for the use of IRIS to manage breeding and evaluation projects were produced. An updated IRIS CD with latest information, and full support, for remote management of genealogy and evaluation data was released. A prototype web access for IRIS was developed to permit global publication of the IRIS in 2001. The web access also integrates IRIS directly with USDA RiceGenes and the US Genetic Resources Information System (GRIN). Partnerships developed with NARS IRRI co-organized the ICIS 2000 international development workshop held at CIMMYT in February 2000. Several Chinese scientists visited IRRI to learn how IRIS could be used for the management of multienvironment trials. We developed a collaborative program to capture pedigrees on recent Chinese rice varieties, including Chinese names, and to deploy IRIS in at least one breeding project in China. Work with the Southeast Asian Shuttle Breeding Network captured historical information and trained users of IRIS. A training workshop for the South Asian Shuttle Breeding Network was held in India to deploy IRIS in the network and facilitate exchange of information on the shuttle of germplasm.

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Table 3. Origin and number of seed lots of imported rice seeds during 2000. Region (country) Shipments (no.) Seed lots (no.) 2,747 29 84 51 1,866 269 595 5,641 Weight (kg) 19.4 0.4 0.2 4.6 47.6 24.3 0.9 97.4

East Asia (3) 8 Europe (2) 2 Latin America (1) 1 South Asia (3) 6 Southeast Asia (5) 11 Sub-Saharan Africa (2) 3 West Asia & North Africa (1) 3 Total 34

Table 4. Distribution of rice shipments from IRRI during 2000. Region (country) Shipments Seed lots (no.) (no.) 84 62 13 31 14 87 100 15 22 428 11,923 2,078 2,041 2,991 1,576 11,779 14,163 1,279 2,629 50,459 Weights (kg) 264.0 182.5 60.1 21.4 9.6 455.4 580.5 41.6 102.2 1,717.3

East Asia (6) Europe (11) Latin America (8) North America (2) Oceania (3) South Asia (6) Southeast Asia (9) Sub-Saharan Africa (8) West Asia & North Africa (5) Total

Seed health testing services
Seed health testing T.W. Mew, S.D. Merca, P.G. Gonzales, C.C. Huelma, and J.O. Guevarra The Seed Health Unit (SHU) processed 34 incoming seed shipments (5,641 seed lots) from 17 countries for post-entry clearance (Table 3) to three IRRI divisions. Untreated incoming seed lots were tested and found to have Bipolaris oryzae (4.6%), Tilletia barclayana (3.3%), Fusarium moniliforme (1.0%), Microchodium oryzae (1.3%), and Sarocladium oryzae (0.1%). Interception of quarantine objects recorded were weed seeds in 0.1% of incoming seed lots (Echinochloa spp., Ischaemum rugosum and Scirpus spp.), insects in 5.1% (Sitophilus oryzae, S. granarius, Sitotroga cerealella, Rhizopertha dominica, Tribolium confusum, and Cryptolestes ferrugineus), seeds with soil (0.9%), and smutted seed (0.3%).

All incoming and outgoing rice seeds were treated with standard ASEAN plant quarantine seed treatment for rice to satisfy plant quarantine requirements. Seed shipments to India and the United States had only fumigation as specified in their import permits. SHU also certified 428 rice seed shipments (50,459 seed lots) to 58 countries worldwide (Table 4). Untreated outgoing seed lots were tested to have S. oryzae (6%), M. oryzae (3%), F. moniliforme (1.5%), B. oryzae (1.3%) and Pyricularia grisea (1.0%). Post-entry quarantine crop-health inspections were made on 7,775 incoming entries and pre-export inspections on 6,134 seed multiplication entries. An online SHU database management system (MS-SQL) is in trial implementation. National program staff from Bangladesh (5), Vietnam (3), and Indonesia, Philippines, and Thailand (1 each) attended the Rice Seed Health for Crop Management Training Course 31 Jul-22 Sep 2000. Five Philippine Plant Quarantine officers completed SHU training on detection, identification, and eradicative seed treatments for T. barclayana in preparation for a Philippine government importation of hybrid rice seeds. NaOCl was tested as pretreatment for the blotter test of seedborne fungi. The pretreatment permitted vigorous growth of seedborne fungi with less seed surface contamination, thereby offering better detection. Partnerships with Philippine Plant Quarantine Service SHU participated in the Training–Workshop on General Plant Quarantine organized by the Philippine Plant Quarantine Service. The SHU, as a model setup on plant quarantine for rice, was shown to the 18 plant quarantine officers from different Philippine regions. Laboratory training was conducted on rice seedborne diseases, other quarantine objects, detection methods, identification, seed treatments, and use of corresponding equipment and facilities.

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Accelerating the impact of rice research

STRENGTHENING PARTNERSHIP WITH NARES East and Southeast Asia 112 Cambodia 112 China 113 Indonesia 114 Lao PDR 114 Japan 115 Myanmar 115 Thailand 115 South Asia 116 Bangladesh 116 India 117 East, Central, and Southern Africa 117 Madagascar 117

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DELIVERY OF KNOWLEDGE-INTENSIVE TECHNOLOGIES: CROP AND RESOURCE MANAGEMENT NETWORK (CREMNET) 118 Extending natural resource management knowledge to farmers: a simple tool for nitrogen management in rice 118 Field evaluation of the LCC technique 118 COLLECTING, EXCHANGING, AND DISTRIBUTING KNOWLEDGE AND INFORMATION ABOUT RICE 118 Scientific publishing 118 Public awareness, visitors, exhibitions, and conferences 120 Library and documentation service 120 Intellectual property (IP) activities 123 HUMAN CAPITAL DEVELOPMENT OF NARES RICE PROFESSIONALS Degree and postdegree training 124 English proficiency and computer skills development 124 Development and implementation of short-term courses 124 PROGRAM OUTLOOK 124 International Programs Management Office (IPMO) CREMNET 124 Communication and Publications Services 127 Training Center 127 142 124

Accelerating the impact of rice research

The impact of rice research on low-income rice producers and consumers is IRRI’s foremost concern. The Accelerating the Impact of Rice Research (IM) program takes results from IRRI research and facilitates its delivery to national agricultural research and extension systems (NARES) partners. IM has four projects: q Strengthening partnership with NARES q Delivery of knowledge-intensive technologies: Crop and Resource Management Network (CREMNET) q Collecting, exchanging, and distributing knowledge and information about rice q Human capital development of NARS rice professionals

Strengthening partnership with NARES
M.A. Bell and staff The year was a period of review and consolidation of the International Programs Management Office’s (IPMO) mandate and responsibilities. IRRI country office procedures were developed into a set of standard operating procedures. East and Southeast Asia
CAMBODIA

Gender and agricultural opportunities Sovith Sin13 and H. J. Nesbitt
Women in Cambodia play a significant role in agricultural production. Approximately 20% of households in the rural areas are headed by women who take responsibility for household expenditure and an increasing percentage of the farm management. Technology introduced by the Cambodia-IRRIAustralia Project (CIAP) has been gender-insensitive. New varieties require no extra labor, and CIAP soil improvement recommendations often result in smaller fertilizer applications. The CIAP integrated pest management (IPM) program recommends a reduction in the level of applied pesticides, thereby reducing health risk and costs. Higher yields have increased labor requirements of both sexes, but threshing machines have reduced the need for hand threshing.

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Training R. Raab and staff
IRRI directly supported more than 6,000 training events (13% for women) for more than 1,600 individuals (12% women) in Cambodia during 19872000. More than 40 Cambodian individuals worked with experienced CIAP advisors in a national research program created by the project. In addition to in-country courses, 350 Cambodians traveled abroad to observe research and management activities and exchange ideas and information with colleagues.

CIAP provided about 250 training opportunities to Cambodian NGO staff members during 19882000. CIAP also played an important role in technical backstopping of NGOs.

Impact of CIAP programs on the Cambodian economy D. Young, R. Raab, R. Martin15, S. Sin, B. Leng16, B Abdon, S. Mot14, and M. Seng17
An evaluation of CIAP looked at the financial benefits to farm households from their adoption of project technologies. The evaluation used a simple with-project and without-project comparison for four phases: q Phase 1, development (1987-94) q Phase 2, adoption (1995-99) q Phase 3, adoption (2000-2010) q Phase 4, plateau (2010-2020) The study found that adoption of CIAP technologies generated significant benefits for farmers. Financial rates of returns for rice are in the range of 35-45%. Farmers who made the change from traditional to improved wet-season (WS) rice production did so without making front-end investments, and the financial benefits outweighed seed and fertilizer costs by a factor of about 1.67. The overall economic rate of return to investment is estimated to be 32%, considering all the benefits and costs over the full life of the investment (1987-2020). The total cost of the project was $24.65 million. The projected increase in rice production is $1,292 million over the 33-year period of study.
CHINA

Varietal improvement S. Mak14 and S. Mot14
Cambodian rice (CAR) varieties selected through the CIAP research program were purified into single line isolates for evaluation in farmers’ fields. More than 5,000 trials and demonstrations with CAR rice were conducted in 359 communes across 18 provinces during 1995-2000. Not all provinces started the demonstration program in 1995 and measurements in 2000 estimated that CAR varieties were cultivated on 194,000 ha in 12 of the 18 provinces of Cambodia—about 11% of the total harvested area in the rainfed lowlands. Farmers' preference for CAR varieties varies from province to province. CAR 3, CAR 4, and CAR 6 were favored overall because of high yield, superior eating qualities, low level of red grains, white grain color, and ease of milling. All three varieties scored better in taste tests than Neang Minh, a local standard variety, and were often sold under that name.

S.Tang

NGOs as partners of IRRI-CIAP C. Norris and H.J. Nesbitt
CIAP strengthened the capacity of key cooperators, namely the Ministry of Agriculture, provincial agricultural offices, and nongovernment organizations (NGOs), to provide technologies for rice-based farming systems. Those groups helped establish CIAP research priorities, took part in the research planning process, conducted station and on-farm trials, and provided direct linkages with the end users of CIAP research.

A China-IRRI work plan meeting was held in June 2000 in Hangzhou. Agreements covered q A collaborative 5-year research and training work plan between the Chinese Academy of Agricultural Sciences and IRRI. q Memorandums of agreement between IRRI and the National Natural Science Foundation of China, Zhejiang University, and Yunnan AAS. IRRI scientists worked in 20 collaborative research activities with scientists from the China Na-

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tional Rice Research Institute (CNRRI) and other institutions. Work covered yield gap, water management, and IPM. Hybrid rice breeding work under the Asian Development Bank-funded Development and Use of Hybrid Rice in Asia Project was organized in CNRRI and Guangxi AAS. A line selected from IR64446 in the IRRI-Yunan AAS shuttle breeding project was named as Dianchao 1. It had a yield of 9.1 t ha-1 (10% more than local hybrid Shenyou 63) in an area of about 2000 ha in Yunnan Province.
INDONESIA

LAO PDR

J. Schiller, B. Linquist, and M. Bell The Lao-IRRI Research and Training Project (LaoIRRI Project) is a long-term project of research development, research support, and training aimed at strengthening the rice research capability within the Lao PDR. Financial support is provided by the Government of Switzerland through the Swiss Agency for Development and Cooperation.

Sustaining high rice yields in intensive lowlands M. Syam
Indonesia’s rice production has stagnated during the last 5 years while population continued to grow at 1.35% y–1. Indonesia’s rice cropping systems are among the most intensive in Asia, and the sustainability of rice production faces challenges from soil and pest problems. The current average yield of lowland rice is 4.7 t ha–1. Some studies indicate declining productivity in some intensively cropped irrigated lowlands; other studies have revealed potential of sustaining and increasing productivity through crop and resource management. Studies in Sukamandi, for example, found that farmers’ rice yield of 6.3-6.6 t ha–1 could be increased to 7.3–8.4 t ha–1. Scientists identified appropriate components of integrated crop management for Sukamandi, including use of the variety Way Apoburu, the addition of 2 t compost of rice straw ha–1, intermittent irrigation (5–6 d rotation), and the use of 10–15-d-old seedlings. The Indonesian Agency for Agricultural Research and Development in collaboration with IRRI developed a 3-year plan of integrated crop management field experimentation in seven rice-producing provinces. Pilot activities started in 2000 and the project will expand in 2001 with farmer-participatory surveys to identify the problems.

Institution development A national network of research centers and scientists engaged in rice research has been established since the start of the Lao-IRRI Project in 1990. The network is formally recognized as the National Rice Research Program of the Lao PDR and involves more than 120 research scientists and technicians, and seven research centers and stations. All research in the Lao PDR is within one agency, the National Agriculture and Forestry Research Institute, Ministry of Agriculture and Forestry. Research program development The development, and adoption by farmers, of improved varieties is one of the technological successes of the National Rice Research Program. By 1999, more than 70% of the WS lowland rice-producing region of the Mekong River Valley was planted to improved glutinous varieties (compared with about 5% in 1990). Nutrient management strategies for the main rainfed-lowland and irrigated areas were developed, with the potential to raise average yields in most areas by at least 100%. Research in the upland environment focused primarily on characterization of production constraints and examination of a range of component technologies. The Rice Biodiversity Project collected more than 13,600 samples of cultivated traditional rices and more than 250 samples of wild rices. A medium-term-storage germplasm bank was established in the Lao PDR.

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Training Five scientists had completed their MS degree studies and four scientists were engaged in upgrading their degree qualifications by the end of 2000. Support for an increasing proportion of the training initiatives has been sought from agencies other than the Lao-IRRI Project.
Collaborative research and training linkages An important activity of the Lao-IRRI Project has been to foster the development of collaborative research and training links with other national and international agencies and networks. Linkages currently include projects supported by the Australian Centre for International Agricultural Research (ACIAR), the United States Department of Agriculture in collaboration with the University of California (Davis), the Shizuoka and Kyoto Universities of Japan, and the International Potash and Phosphate Institute. The Lao National Rice Research Program has full membership in the Upland Rice Research Consortium and affiliate status in the Rainfed Lowland Rice Research Consortium. Linkages with the Thai National Rice Research Program and the Thai Department of Agriculture also exist.
JAPAN

q

were sent to 171 people by mail and to 450 people through e-mail. Ninety books and 631 titles of journals were sent to IRRI Library. A total of 1,546 Japanese rice references from 358 journals were assigned with key words and indexed.

MYANMAR

The 4-year Community-Based Natural Resource Management Project in Myanmar ended. The Myanmar Agriculture Service subsequently identified a staff member to act as the IRRI coordinator to ensure contact between the two institutions.

Nutrient management A. Garcia, U Aye Swe, U Soe Myint, and U Hla Tin

H. Hibino

National policy and environment for rice Government offices, including the Ministry of Agriculture, Forestry and Fisheries, will undergo reorganization in 2001. Activities to support IRRI in Japan during 2000 included q Extensive communication with scientists in national institutions and universities. q Displays of IRRI publications and posters at international events at Tokyo and Yokohama. q A review of the Japan-IRRI Shuttle Research at IRRI. The review panel concluded the project was valuable for providing opportunities for young Japanese, IRRI, and NARS scientists to participate in collaborative research programs for advanced sciences. q Distribution of four issues of the IRRI Hotline, as a condensed version in Japanese. IRRI Hotline, and News About Rice and Peoples

Urea fertilizer is the only source of N fertilizer in Myanmar. Results of on-farm studies during the 1999-2000 DS showed that urea applied as urea tablets using a farmers’ fertilizer rate (57 kg N ha–1) produced significantly higher yields than granular urea. The labor requirements for application of the urea tablet, however, may limit wide acceptance by farmers. On-farm experiments showed that the applica–1 tion of 90 kg N ha produced significantly higher grain yield than the farmers’ practice of 57 kg –1 N ha . When farmyard manure or liquid fertilizer (biosuper fertilizer) was added to the farmers’ rate –1), (57 kg N ha grain yield also increased significantly.
THAILAND

Varietal improvement S. Boriboon
Four rice elite lines were officially named and released: q SPTLR84051-32-2-4 as Sanpathong 1 q IR62558-SRN-17-2-1-B as Surin 1 q PSL91014-16-1-5-1 as Phitsanulok 1 q PTT90071-93-8-1-1 as Pathum Thani 1 Sanpathong 1 and Surin 1 are blast- and bacterial blight-resistant, high-yielding, photoperiod-insensitive varieties released for north and northeast Thailand.

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Phitsanulok 1 and Pathum Thani 1 are blast- and brown planthopper-resistant, high-yielding, and photoperiod-insensitive varieties. Phitsanulok 1 is recommended for the irrigated area in the lower northern region. Pathum Thani 1 is a fragrant rice possessing KDML 105 grain type. It was released in the Central Plains.

Workshops, meetings, and training Workshops organized included q International Workshop on Direct Seeding in Asian Rice Systems: Strategic Research Issues and Opportunities, q Regional Working Group and Technical Team Meeting on the Korat Basin Ecoregional Project, and q 4 th Annual Meeting of the Council for Partnership on Rice Research in Asia (CORRA). A Rice Exhibition and Research Seminar was organized to coincide with the celebration of the 40th IRRI anniversary and 40 years of Thai-IRRI collaboration. A training course on Germplasm Evaluation and Utilization in Rainfed Rice ran 14 Sep–20 Oct at Ubon Rice Research Center.
South Asia
BANGLADESH

IRRI collaboration in Bangladesh reached a record height in number of activities and research staff time. Fifty-nine different international scientists spent 663 d (39 were IRRI scientists for 493 d) in Bangladesh to contribute to the collaboration. Poverty Elimination Through Rice Research Assistance (PETRRA), a project started in 1999, contributed mostly to the large pool of scientists. In addition to PETRRA-driven activities, IRRI research collaborated through 20 specific projects with financial support from nine different donors. A strategic dialogue on IRRI-Bangladesh partnership and future directions took place at Dhaka in October 2000, with participation of senior Bangladesh Rice Research Institute (BRRI), Bangladesh Agricultural Research Council, and IRRI scientists plus key representatives from other stakeholders, including NGOs. Among issues considered, continued scientific capacity building, upgrading research capacity and facilities for application of modern biotechnology and hybrid rice technology, and enhancing germplasm exchange services with IRRI were considered critical.

Poverty Elimination Through Rice Research Assistance N. Magor
PETRRA, a project funded by the Department for International Development (DFID), UK, with the purpose of increasing productive potential of ricebased farming systems in Bangladesh began in September 1999. The goal is to increase domestic rice production, and incomes, by 2008, and contribute toward a 50% reduction in rural and urban poverty by 2015. The 5-year project is managed by IRRI in partnership with the BRRI. The success of the project will be measured in terms of technology development and for direct impact on the livelihoods of farm households and rice consumers. PETRRA will facilitate development of a research system that includes resource-poor farm households in the research process. The approach will be environmentally responsible and gender sensitive. PETRRA is guided by a Steering Committee (supported by a Technical Committee), which is chaired by the Secretary of Agriculture. Membership on the Steering Committee is from research in-

S.I. Bhuiyan Bangladesh produced about 23.1 million t of milled rice in 2000, which was 16% higher than the previous all-time high production of 1999. By 2020, the demand for rice in Bangladesh is predicted to increase from the current 23 million t to more than 30 million t. Rice yields will need to increase by 50% to maintain food security without substantial imports. The availability of suitable modern rice production technology for the dry season, which caused a shift of rice areas from the low-productive deepwater and aus systems to the higher yielding boro system, is the most important factor contributing to production growth. Boro rice output increased from 35% of total rice 10 years ago to 48% of total rice in 2000.

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stitutions in Bangladesh, IRRI, Philippines, Bangladesh-IRRI Office, DFID, and prominent NGOs within Bangladesh. During PETRRA’s first year, there was major emphasis on identification of resource-poor, demand-driven researchable issues. Consultation was completed across 13 districts representing different major ecosystems. There was also high-level consultation and debate on policy issues and detailed discussion of themes emerging through the villagelevel consultations. PETRRA has a major subproject on seed health that is conducted jointly with IRRI, BRRI, the Rural Development Academy, and four NGOs. Principal emphasis is on farmer-level seed quality. Other major subprojects are hybrid development, seed production and dissemination, salinity tolerance in varietal development for the coastal region, improved crop nutrient management, and policy micro-studies on access to quality inputs and livelihoods.
INDIA

Center for Applied Research on Rural Development (FOFIFA) scientists, development organizations (government, NGO, private sector), and farming communities to develop and promote new rice varieties and production technologies to farmers in target areas. Prototypes of agricultural machinery, using animal traction and motors, designed at IRRI and elsewhere have been tested and adapted to conditions in Madagascar. The project produced designs and production manuals for machine manufacturers and technical bulletins for farmers on how to use and maintain the machines. Farmers, technicians, and trainers were trained on using bullocks for animal traction at Tulear (Menabe and Bezaha), Fianarantsoa, and Mahajanga provinces. Adequate consideration was given to labor displacement and gender issues by evaluating all technologies for their gender effects. Alternative employment was created through diversified farming and postharvest processing of various products.

R.K. Singh The IRRI-India office provided logistical support to 724 scientists from India and abroad for their participation in IRRI-sponsored activities. The office organized three major review and planning meetings, two workshops, two training courses, and three study tours. Sixty-three IRRI scientists made monitoring visits in India. A major public awareness activity was held at India International Centre, New Delhi, 25 Sep 2000 with 45 participants from the Indian Council of Agricultural Research, NARS, and the news media. East, Central, and Southern Africa
MADAGASCAR

Delivery of knowledge-intensive technologies: Crop and Resource Management Network (CREMNET)
V. Balasubramanian CREMNET is designed to act as a catalyst to NARES partners in facilitating the identification, free exchange, participatory evaluation, and promotion of promising technologies in rice farming. Extending natural resource management knowledge to farmers: a simple tool for nitrogen management in rice V. Balasubramanian, A. C. Morales, R. T. Cruz, N. N. De, P. S. Tan, and Z. Zaini Inadequate or excessive amount, or improper timing of N application may lead to N losses and poor N use efficiency in flooded rice. The leaf color chart (LCC) is a simple and inexpensive tool that can improve farmers’ decision making in N management for rice (IRRI Program Report for 1998). The LCC was developed by IRRI and the Philippine Rice Research Institute (PhilRice) from a Japanese prototype. The chart contains six gradients of

V. Balasubramanian

Farm machinery development and adaptation The IRRI team for the Madagascar-IRRI-United States Agency for International Development Environment and Agriculture Project (1998-2001) worked in close collaboration with the National

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green from yellowish green (No.1) to dark green (No.6) and can effectively guide N applications in rice fields. Field evaluation of the LCC technique. We worked with collaborators in different countries to motivate farmers to try the LCC and gather their feedback. Three efficiency criteria were used to evaluate the LCC method: q grain yield, q agronomic efficiency of applied N, defined as the increase in kg of grain yield over control per kg N applied, and q partial factor productivity of N, defined as total grain yield kg N–1 applied. On-farm trials demonstrated the advantage of using the LCC to promote need-based N application in rice. We observed three situations: Case 1: An increase in grain yield but with higher N fertilizer use. The efficiency values were similar for both farmers’ and LCC methods (Table 1). This confirmed the local farmer’s efficient use of N fertilizers. Case 2: Less N fertilizer use but with rice yields maintained at current high level. Here, grain yields were similar for both farmer and LCC methods. However, the amount of N used was much lower and N use efficiency was much higher for the LCC (Table 1). In this case, the farmer’s N fertilization practice has to be improved. Case 3: An increase in grain yield and a reduction in N fertilizer use. Nitrogen use efficiency was much higher in the LCC method than in farmers’ practice (Table 1). In this case, a lot of improvement in farmers’ practice is needed to save on N fertilizer and to increase grain yield. Our conclusions are: q The LCC helps farmers to monitor crop N status, irrespective of N sources (organic, biological or chemical fertilizers). It is an environment-friendly tool. q The successful adaptation and use of the LCC technique will promote the timely and efficient use of N, minimize N losses and hence fertilizer-induced pollution of water sources, and produce healthy plants that require less use of pesticides. q Average savings in N fertilizer use range from 0 to 53 kg N ha–1 in flooded rice.

q

q

We need to learn how farmers internalize the new N management knowledge in rice or in other crops. Strict maintenance of the color shades is important to ensure reliability of the LCC. We have to develop a quality certification program for charts produced by various agencies in different countries, using the IRRI-produced LCC as standard.

Collecting, exchanging, and distributing knowledge and information about rice
W. Padolina, G. Hettel, B. Hardy, D. Macintosh, S. Inciong, M. Movillon, and M. Ramos IRRI’s mandate requires that the Institute publish and disseminate research findings and promote current rice research knowledge to scientists worldwide to enable them to do their research more effectively. Scientific publishing IRRI’s four web sites—the IRRI Home site (www.cgiar.org/irri), Riceweb, Riceworld, and the IRRI Library site—continue to grow in popularity. We had nearly 210,000 visitors to the web sites during 2000. The visitors made more than 780,000 hits, or movements within the sites. Clients downloaded more than 100,000 files of popular information sources, such as installments of the discussion paper series, stories from the 1999-2000 annual report, sections of the International Rice Research Notes and annual program reports, and IRRI-developed software (e.g., more than 1,000 downloads of the popular IRRISTAT program for statistical analysis). During the year, the web sites were enhanced by the addition of q electronic versions of the three 2000 issues of the International Rice Research Notes (www.cgiar.org/irri/irrn.htm), the 1999 Program Report (www.cgiar.org/irri/ 99ProgramReport/99programreport.htm) and recent IRRI conference and workshop proceedings (www.cgiar.org/irri/absidx.htm). q new sections devoted to rice genomics (www.cgiar.org/irri/genomics/), rice

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Table 1. The effect of leaf color chart-based N management on grain yield, N use efficiency, and saving of N in farm-level evaluation studies, 1996-99. Case and treatmenta N used (kg ha–1) Grain yield (t ha–1) AENb PFP-Nc N saved (kg ha–1)

Case 1: Increase in rice yields with higher N fertilizer use. Philippines — Maligaya: TPR, 1998 DS (14 farms) Control 0 3.8 b – – – Farmer practice 116 5.7 a 19 a 49 – LCC-4 130 6.0 a 19 a 46 –14 Case 1: Increase in rice yields with higher N fertilizer use Philippines — Maligaya: TPR, 1999 DS (9 farms) Control 0 3.3 b – – – Farmer practice 121 5.1 a 15 a 42 – LCC-4 135 5.3 a 16 a 39 –14 Case 2: Less N fertilizer use with rice yields maintained at current level. Philippines — Maligaya: TPR, 1996 WS (17 farms) Control 0 3.3 c – – – Farmer practice 101 4.2 a 10 c 41 – SPAD-32 N 73 4.2 a 14 b 57 28 LCC-4 48 4.2 a 21 a 87 53 Case 2: Less N fertilizer use with rice yields maintained at current level. Philippines — Maligaya: TPR, 1997 WS (12 farms) Control 0 3.5 c – – – Farmer practice 97 4.5 a 10 a 46 – LCC-4 87 4.3 b 9a 49 10 Case 2: Less N fertilizer use with rice yields maintained at current level. Philippines — Maligaya: TPR, 1998 WS (11 farms) Control 0 3.4 b – – – Farmer practice 78 4.0 a 9b 51 – LCC-4 33 3.9 a 20 a 117 45 Case 2: Less N fertilizer use with rice yields maintained at current level. Philippines — Maligaya: TPR, 1999 WS (11 farms) Control 0 3.7 b – – – Farmer practice 74 4.5 a 12 b 61 – LCC-4 46 4.7 a 19 a 102 28 Case 2: Less N fertilizer use with rice yields maintained at current level. Vietnam — Cai Lay District: B-WSR, 1997 DS (14 farms) Farmer practice 107 4.9 a – 46 – LCC-3 64 4.9 a – 77 43 Case 2: Less N fertilizer use with rice yields maintained at current level. Vietnam — Cai Lay District:B-WSR, 1998 DS (10 farms) Farmer practice 88 7.0 a – 79 – LCC-3 70 7.2 a – 103 18 Case 2: Less N fertilizer use with rice yields maintained at current level. Vietnam — Cai Lay District:B-WSR, 1998 DS (28 farms) Farmer practice 120 5.2 a – 44 – LCC-3 82 5256 a – 64 38 Case 2: Less N fertilizer use with rice yields maintained at current level. Vietnam — Cai Lay District:B-WSR, 1999 DS (7 farms) Farmer practice 99 6.3 a – 64 – LCC-3 70 6.3 a – 90 29 Case 2: Less N fertilizer use with rice yields maintained at current level. Indonesia — Simalungun District, North Sumatra: TPR, 1998 DS (60 farms) Farmer practice 171 5.3 a – 31 – LCC-4 135 5.4 a – 40 36 Case 2: Less N fertilizer use with rice yields maintained at current level. Indonesia — Deli Serdang District, North Sumatra: TPR, 1998 DS (60 farms) Farmer practice 199 5.7 a – 28 – LCC-4 157 5.6 a – 36 42 Case 3 An increase in rice yields and a reduction in N fertilizer use. Philippines — Maligaya: B-WSR, 1998 DS (6 farms) Control 0 3.6 c – – – Farmer practice 151 4.5 b 6b 30 – LCC-3 125 5.1 a 14 a 41 26 Case 3: An increase in rice yields and a reduction in N fertilizer use. Vietnam — Omon and Thotnot Districts: B-WSR, 1999 DS (20 farms) Farmer practice 108 4.4 b – 41 – LCC-3 98 4.8 a – 49 10 Case 3: An increase in rice yields and a reduction in N fertilizer use. Vietnam — Huyen District: B-WSR, 1999 DS (18 farms) Farmer practice 98 4.6 b – 47 – LCC-3 80 4.9 a – 62 18
a

TPR = transplanted rice, B-WSR = broadcast wet-seeded rice, WS= wet season, DS= dry season. LCC-4 is threshold for TPR; LCC-3 is threshold value for BWSR. bAgronomic efficiency of N. cPartial factor productivity of N.

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bioinformatics (www.cgiar.org/irri/ bioinformatics/), decision support tools (www.cgiar.org/irri/Troprice/) and software downloads (www.cgiar.org/irri/ SoftwareDownloads.htm). An electronic bulletin debuted on the in-house IRRI intranet in April featuring latest news, announcements, and experimental video clips of IRRI activities. Credit card sales of IRRI books continued successfully on the Internet via the web site of Germany-based book vendor TRIOPS (www.cgiar.org/ irri/TRIOPS2.html). Sixteen titles were produced and distributed, including seven IRRI books, four installments of the IRRI discussion paper series, and one installment of the limited proceedings series. One of the books, Redesigning rice photosynthesis to increase yields, was a dual imprint with Elsevier Science. Three issues each of the International Rice Research Notes and Rice Literature Update were printed and distributed. A bibliography is provided in the section on publications and seminars near the end of this program report. More than 139,000 images (slides and prints) in the IRRI archives dating back to 1960 were assessed, classified, cataloged, and indexed. Of these, about 3,500 images (which provide a good crosssection of the best visuals on rice subject matter in the collection) were scanned and made available for searching and downloading via Institute computers using the Canto Cumulus system. Public awareness, visitors, exhibitions, and conferences The Public Awareness (PA) and the Visitors, Exhibition, and Conference Services (VECS) were formally merged during 2000. The combined unit handles and coordinates PA activities, visitors, public events, exhibits, and the Riceworld museum. The Riceworld Museum was closed for part of 2000 (after a fire in late 1999) but reopened in time for the Institute’s 40 th anniversary activities in April. The Chandler Hall Auditorium, which was also damaged by the fire, remained closed throughout 2000 and will reopen in early 2001. Public awareness. PA activities were dominated by two major events in 2000: q 40 th anniversary celebrations: Activities included the International Rice Research Conference, festivities on 4 April, and the

International Rice Genetics Symposium in October. q Development of vitamin A-enriched golden rice in Switzerland. Since the breakthrough was first announced in January, the story gained an extraordinary amount of publicity. IRRI benefited extensively as the story generated strong media interest in rice research, biotechnology, and food production in general. Other PA activities were tied to the biotechnology debate in the Philippines and Asia, and included a wide range of exhibits and events. The unit produced q 28 press releases, 27 photo releases, and four editions of the IRRI Hotline; q more than 100 broadcasts of The IRRI Hour radio show; q the 1999-2000 annual report (The Rewards of Rice Research) and 2001 wall calendar (Rice Science for a Better World), and q a new PA internet homepage (Media Hotline: www.cgiar.org/irri/pa/); Visitors, exhibitions, and conferences. About 50,000 visitors came to IRRI during 2000 (up from 38,000 in 1999), including 10 state ministers, 35 ambassadors and members of the diplomatic corps, and 15 representatives of the various donor- and international organizations such as the UNDP, FAO, ADB, and JICA. The Institute hosted or cohosted 35 regional and international conferences, workshops, symposia, reviews, and meetings attended by more than 1,900 participants from at least 51 countries (Table 2). Library and documentation service More than 8,000 references were added to the rice bibliography database during 2000, bringing the total to more than 188,300. The on-line catalog grew to 60,715 bibliographic records. The International Bibliography on Rice Research, 1951-2000 was published in CD-ROM format in December. The library added 277 rice dissertations to its collection, most of which came from China and major European countries, and acquired 33 video cassettes for the Audio-Visual Learning Center. The main library collection now contains 116,655 monographs and 1,536 active serial titles. The library filled requests from 56 countries involving current awareness, reference services, com-

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IRRI program report for 2000

Table 2. International and regional conferences, workshops, symposia, and meetings hosted or cosponsored by IRRI in 2000. Date Title Venue Participants (no.) 12 Countries (no.) 6

3-4 Feb

Asia-Pacific Workshop on the Development of Technical Advisory Notes (TAN) on technologies resulting from IFAD-funded agricultural research Reaching Toward Optimum Productivity (RTOP) Workshop The Irrigated Rice Research Consortium Planning Meeting Workshop on the Impact on Research and Development of Sui Generis Approaches to Plant Variety Protection of Rice in Developing Countries (CORRA PVP Workshop) Workshop on Data Analysis and Interpretation for the Participatory Plant Breeding and Gender Analysis Project Systemwide Program for Integrated Pest Management Novartis Foundation Symposium IRRC 2000: Rice Research for Food Security and Poverty Alleviation Dialogue for establishing partnerships between public-sector research institution and seed industry in private, NGO, and cooperative sectors for production and marketing of hybrid rice seed Korea-IRRI Workplan Meeting Biological Weed Control in Rice Workshop Discussion meeting on next phase of India hybrid rice project to be submitted to ADB Study tour on hybrid rice in India Review Meeting of the Japan-IRRI Shuttle Research Project China-IRRI Collaborative Workplan Meeting Constraints to increasing rice production in Asia: insights from study on farmers’ perceptions CORRA Planning Meeting on building institutional capacity to manage and exchange rice varieties among nations in the new world trade regime The Irrigated Rice Research Consortium Ad Hoc TAC Meeting Rice IPM Network Fourth Review and Planning Workshop CGIAR Women’s Leadership and Management Development Course Third Technical and Steering Committee Meetings

IRRI

5-9 Feb 14-15 Feb 16-18 Feb

IRRI IRRI IRRI

23 19 83

10 3* 20

28 Feb 11 Mar 13-17 Mar 27-29 Mar 31 Mar 3 Apr 18 Apr

IRRI

30

3

IRRI IRRI IRRI IRRI

21 33 243 33

10 7 35 1

27 Apr 10-12 May 12 May 19-11 May 29-31 May 1-2 Jun 7-9 Jun

IRRI IRRI IRRI India IRRI China India

29 33 11 23 74 64 35

2 10 5 7 2 2 7

22-23 Jun

IRRI

23

13

30 Jun 3-6 Jul 9-15 Jul 31 Jul3 Aug

IRRI Thailand IRRI Indonesia

13 40 21 18

3 10 9 8

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Table 2 continued. Date Title Venue Participants (no.) 53 Countries (no.) 12

31 Jul4 Aug 18-19 Aug

The Irrigated Rice Research Consortium IPMNet/INMNet/HRNet Joint Technical and Steering Committee Meetings Third CREMNET-India Workshop-cum-Group Meeting on Direct Seeding and Seeders in Rice Impact Symposium - on Exploiting Biodiversity for Sustainable Pest Management Long-Term Phosphorus Experimental Data Synthesis Workshop Rice IPM Network Message Design Workshop for Campaign on Motivating Farmers to Reduce Unnecessary Insecticide Sprays Upland Rice Research Consortium Review and Synthesis Meeting Reversing Trends of Declining Productivity (RTDP) Workshop Dialogue on IRRI Bangladesh Collaboration A mini-symposium on Improving Tolerance for Abiotic Stresses in Rainfed Lowland Rice Rainfed Lowland Rice Research Consortium (RLRRC) Steering Committee Meeting IRGS 2000 International Conference on The Impact of Agricultural Research for Development in Southeast Asia Fifth Seminar on GIS and Developing Countries, GISDECO, GIS Tools for Rural Development 4th Annual Meeting of the Council for Partnership on Rice Research in Asia (CORRA) Inception Meeting for Breeding for Iron-Dense Rice: A Low-Cost Sustainable Approach to Reducing Anemia in Asia Review and Planning Meeting on Rice Seed Health Improvement for Increasing Yield and Reducing Pest Pressures in Bangladesh International Conference on Increasing Rice Productivity: Implications for Pest Management and Satellite Consultative Workshop on Effective and Sustainable Use of Pest Management in Developing Countries

Indonesia

India

40

1

21-23 Aug 28 Aug1 Sep 30 Aug1 Sep 4-8 Sep 26 Sep6 Oct 1 Oct 21-22 Oct 22 Oct 23-27 Oct 24-26 Oct

China IRRI Thailand

52 9 28

7 6 3

IRRI IRRI Dhaka IRRI IRRI IRRI Cambodia

40 10 17 53 20 500 158

11 6 2 8 6

9

2-3 Nov 6-7 Nov 14-16 Nov

IRRI

99

15

Thailand IRRI

21 24

14 7

25-26 Nov

Bangladesh

62

3

27 Nov01 Dec

China

13

19

122

IRRI program report for 2000

puterized literature searches, document delivery by e-mail or through conventional means, training of librarians (two from Bhutan in April), and book binding. The Innopac computer system was upgraded with three releases. New hardware and software (MA32, Ariel version 2.2, ProCite 5) were purchased to improve information delivery. Cataloging of free full-text electronic resources started in August 2000. Clients can now utilize these resources through direct links created on the on-line catalog. Updating of The International Directory of Rice Workers began in 2000 and will be available on the library web site in early 2001 (ricelib.irri.cgiar.org/). Intellectual property (IP) activities IRRI undertook the second phase of its intellectual property management review (IPMR) and intellectual property (IP) audit in 2000. Phase II focused on the IP implications of q germplasm-related technologies deployed by IRRI, q functional genomics and bioinformatics activities carried out by IRRI researchers, q the new plant type, and q utilization of third-party proprietary technologies to enhance the nutritional value of rice. The results of phase II inquiries indicated that IRRI’s capacity in trait discovery, itself and through its NARS partners, is an important inventive activity. Concluding that there are limitations to a policy of defensive registration, phase II canvassed IP management implications of these issues, addressing the extent to which defensive publication or defensive registration might be utilized to deal with some IP problems. One theme running through the review was the necessity for IRRI to consider IP management in the context of its membership in the CGIAR as a whole. Council for Partnership on Rice Research in Asia. IRRI hosted a workshop on the impact on research and development of sui generis approaches to plant variety protection of rice. Participants came from the CORRA, the Global Forum on Agricultural Research, and the Asia Pacific Association of Agricultural Research Institutions. The USAID,

Rockefeller, and The Netherlands Ministry of Foreign Affairs provided funding. Focusing on the needs for capacity building in light of the new plant variety protection (PVP) regulations in Asia, the workshop included a major case study of the International Network on Genetic Evaluation of Rice (INGER) and examined the question of how PVP and related IP legislation affect the flow of germplasm and access to materials and information. The workshop proceedings, Plant Variety Protection for Rice in Developing Countries: Impacts on Research and Development, can be found on the Internet at www.cgiar.org/irri/PVP/PVPindex.html. A joint IRRI-CORRA workgroup developed an IRRI-NARS institution-building proposal aimed at adapting INGER and Genetic Resources Center (GRC) to the emerging sui generis PVP regimes. During the CORRA annual meeting in November in Thailand, the proposal was approved and adopted as an official CORRA project proposal. Improvements on the internal process. Making the office of the Deputy Director General-Partnerships (DDG-P) a focal point for IP administration at IRRI had significant implications for the procedures by which IP-related cases are considered, processed, filed, communicated, and stored. The IPMR identified a need to consolidate the DDG-P office as one in-house single-door IP unit in charge of handling IP issues and acting as a depository of IP documents. The office is now a central depository for a range of documents related to IP administration. During 2000, the DDG-P office drafted an IP primer, initiated an IP Awareness Program, and finalized the IRRI IP handbook, which includes briefs on policy, descriptions of institutional structures and procedures of IRRI IP administration, explanations on the IRRI databases on Third Party IP and IRRI research products, and a compendium of administrative forms and templates. The priorities of the IRRI IP administration are to ensure that all materials leaving IRRI are accompanied by Material Transfer Agreements, featuring provisions to protect the interests of IRRI and the clients it has been mandated to serve. A full-time intellectual property rights specialist will be on board by March or April 2001.

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Human capital development of NARES rice professionals
P.L. Marcotte and staff IRRI responds to and anticipates the needs of national rice research systems for trained manpower through its Human Capital Development Project. The activity evolved over almost 40 years, simultaneously addressing both the human resource development goals of NARS and fulfilling IRRI’s global mandate. Degree and postdegree training A total of 126 rice scientists and professionals participated in IRRI’s degree and postdegree on-thejob training program in 2000 (Table 3). They represented 26 countries in Asia, Africa, Europe, and North America. Sixty-four of the scholars and onthe-job trainees finished their program during the year: 22 completed their PhD program, 6 the MS program, and 36 their respective on-the-job trainings or internships (Table 4). English proficiency and computer skills development IRRI scholars, staff members, and family members participated in courses in basic and advanced English, English for agriculture, self-editing, and scientific writing during the year. Two courses were offered to develop computer skills. Development and implementation of shortterm courses Short-term group training courses for rice scientists and professionals were conducted either at IRRI or at venues in-country. Group training (headquarters or on-campus). During the year, 95 scientists, representing 14 countries in Asia, Africa, and Europe, participated in 11 group-training courses at IRRI (Table 5). Collaborative in-country training. Collaborative in-country training has focused on national concerns and bringing training to more scientists at less cost. IRRI trained 590 NARS scientists through 20 incountry group training in collaboration with national institutions. Two courses, Genetic Evaluation and Utilization for Rainfed Lowland Rice offered in Thailand and Hybrid Rice Breeding offered in

China, were international courses that trained 27 scientists from 10 Asian countries. Eighteen other courses were national offerings requested by interested NARS. Training materials development. We developed new training materials during the year to support courses on geographic information system modeling, genetic evaluation and utilization, rice seed health, use of information technology (IT), presentation skills, and multiagent simulation modeling.

Program outlook
The new Medium-term Plan integrates much of the old program on Accelerating the Impact of Rice Research (IM) with a project Facilitating Rice Research for Impact. With the merger of the Training Center, CREMNET, and the IPMO, an entity is created to provide support for projects such as the Irrigated Rice Research Consortium. CPS, Library, and Computer Services activities will move from the research matrix as essential support activities. International Programs Management Office (IPMO) IRRI’s investment in countries and regional staffing patterns will be reviewed during 2001. A major activity to support this review is an information database of in-country activities, which was developed during 2000. CREMNET CREMNET activities will be integrated with those of other nutrient management researchers. Activities will continue to refine the chlorophyll meter technique. Village-level evaluation and promotion of the LCC, impact evaluation of the LCC method in Vietnam, and the evaluation of controlled-release fertilizers for hybrid rice, rice-rice, and rice-wheat systems will continue. Development and adaptation of technologies for integrated crop management for DSR and the refinement and promotion of drum seeders will continue in four countries. Tropical rice checks, a location-specific package of improved technologies for sustaining high rice productivity in the irrigated ecosystem, will be developed and evaluated in one country.

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IRRI program report for 2000

Table 3. Participants in degree and postdegree training at IRRI during 2000.

PhD scholars
Alam, Murshed Rasul, Noorain M. Li, Xiangmin Liu, Bin Liu, Jinxiang Mingfu, Zhao Zhong, Daibin* Fu, Binying* Cui, Kehui* Xu, Jianlong* Li, Luping* Ziqi, Wang* Lu, Wenjing* Jianli, Wu* Bagali, Prashanth G. Naranayan, Narayanan N. Singh, Pradeep Kumar Sreevidya, V. S. Dey, Moul* Kaur, Jatinder* Rangan, Latha* Mitra, Sudip* Mathan, Natarajan* Muhsin, Muhammad Abdullah, Buang* Hosseini Salekdeh, Seyed G. Moradi, Foad Moumeni, Ali Sattari, Majid Fallah, Allahyar* Kobayashi, Sohei Samejima, Hiroaki Sugiyama, Nobuko Uga, Yusaku Bangladesh Bangladesh China China China China China China China China China China China China India India India India India India India India India Indonesia Indonesia Iran Iran Iran Iran Iran Japan Japan Japan Japan Naoyoshi, Kawano* Ramanantsoanirina, Alain Mari Andrianilana, Fidelis J.* Htet, Kyu* Thet, Khin Maung* Joshi, Ganesh Raj Regmi, Anant Prasad Belder, Paul Maji, Alhassan T. Arif, Anjum Arif, Muhammad Faiz, Faiz Ahmad* Hafeez, Md. Mohsin Ijaz, Muhammad Borines, Lucia M. Enriquez, Emilie C. Lumbo, Susanita G. Rubia, Leila G. De Vasconcelos, Marta Wilton Mnzava, Moses N.W. Linwattana, Grisana Nieuwenhuis, Pailin Graw, Stephen M. Cuong, Ngo Luc Huu Ho, Nguyen Le, Cam Loan Nguyen, My Hoa Nguyen, Thi Ngoc Hue Nguyen, Van Hong Thanh, Duong Ngoc Tran, Chi Thien Truong Van, Tuyen Thuy, Nguyen Hong* Le, Thi Phuong* Japan Madagascar Madagascar Myanmar Myanmar Nepal Nepal Netherlands Nigeria Pakistan Pakistan Pakistan Pakistan Pakistan Philippines Philippines Philippines Philippines Portugal Tanzania Thailand Thailand USA Vietnam Vietnam Vietnam Vietnam Vietnam Vietnam Vietnam Vietnam Vietnam Vietnam Vietnam

MS scholars
Jensen, Morten Shoatatek, Negussie Singh, Bhupinder Pal Varghese, Pulichal A.* Suganda, Hussein Widowati, Ladiyani Retno Sattari, Majid* Sekiya, Kazumi Rakotomalala, R. Mbolarinosy* Denmark Ethiopia India India Indonesia Indonesia Iran Japan Madagascar Bhattarai, Kiran Joshi, Madan Raj Upadhyay, Bhawana De Vries, Sander C.* Avendano, Bita S.* Pantua, Sheila Marie E.* Falvo, Daniel J. Ngo, Dang Phong Thao, Hoang Thi Bich Nepal Nepal Nepal Netherlands Philippines Philippines USA Vietnam Vietnam

Postdegree on-the-job trainees
Islam, Mirza Mofazzal Rumena, Yasmeen* Mobarak, Sarware M.* Chakravorty, Bhaskhar* Tshethar, Karma* Zangpo, Dawa* Choden, Sangay* Gyamtsho, Thinley* Hu, Fengyi Wen, Jiang Parani, Madasamy* Bangladesh Bangladesh Bangladesh Bangladesh Bhutan Bhutan Bhutan Bhutan China China India Pathak, A.R.* Nath, Palash Deb* Singh, Hari* Devasenapathy, P.* Ventakaraman, N.S.* Singh, Chauhan* Singh, Hawa* Susilawati, S.* Wahab, Ismail* Jamil, Ali* Soedardjo, Widyantoro* India India India India India India India Indonesia Indonesia Indonesia Indonesia

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125

Suharno, S.* Nurawan, Agus* Jayasamudera, Dede J.* Suhaya, Yok* Helmi, H.* Thamrin, Mohammad* Daradjat, Aan A.* Hidajat, Jan Rachman* Phengchanh, Somphet* Chee, Fong Tyng Bhandari, Hem Singh* *Completed training in 2000.

Indonesia Indonesia Indonesia Indonesia Indonesia Indonesia Indonesia Indonesia Lao-PDR Malaysia Nepal

Interns
Schlosser, David* Abdel Bary, Doaa Ahmed* Widharto* Ponsioen, Thomas Christian* De Ponti, Tomek* Fournier, Anselme* Ta, Van Thu* Canada Egypt Indonesia Netherlands Netherlands Netherlands Vietnam

Table 4. Number of scholars/postdegree trainees who completed their training in 2000. Type I Region/Country PhD MS PhD Type II MS Type III ND/Interns

Total

Africa Egypt Madagascar
Sub-total

0 0 0

0 0 0

0 1 1

0 1 1

1 0 1

1 2 3

Asia Bangladesh Bhutan China India Indonesia Iran Japan Lao-PDR Myanmar Nepal Pakistan Philippines Vietnam
Sub-total

0 0 8 5 1 0 1 0 0 0 0 0 1 16

0 0 0 1 0 0 0 0 0 0 0 2 0 3

0 0 0 0 0 1 0 0 2 0 1 0 1 5

0 0 0 0 0 1 0 0 0 0 0 0 0 1

3 4 0 8 13 0 0 1 0 1 0 0 1 31

3 4 8 14 14 2 1 1 2 1 1 2 3 56

Europe Netherlands Switzerland
Sub-total

0 0 0

1 0 1

0 0 0

0 0 0

2 1 3

3 1 4

North America Canada
Sub-total GRAND TOTAL

0 0 16

0 0 4

0 0 6

0 0 2

1 1 36

1 1 64

Type I - MS & PhD scholars, thesis research only at IRRI Type II - MS & PhD scholars, coursework and thesis at IRRI Type III - On-the-job/Nondegree trainees, interns

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IRRI program report for 2000

Table 5. Group trainees (no.) at IRRI by coursea, region, and country, 2000. Region Country Basic Intro to Advanced GIS IVP RSHCM Intro to G×E EDDA SAS EDDA Modeling IRRISTAT Analysis Analysis of Unbalanced. . . Use of MAS IT Total

Africa Europe Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Total
a

Uganda France Bangladesh Cambodia China India Indonesia 10 Lao-PDR Malaysia Myanmar Philippines Taiwan Thailand Vietnam 10

1 1 2 1 2 1 1 1 1 1 3 1 2 1 1 3 3 3 15 1 2 6 1 2 2 3 1 3 1 1 3 1 3 3 1 1 1 2 1 6 1 3 11 9 2 1 1 9 1 1 1 11 8 2 16

1

1 2

1 1 8 9 4 10 21 6 2 2 3 4 12 12 95

Basic EDDA = Basic Experimental Design and Data Analysis; Intro to SAS = Introduction to SAS for Windows; Advanced EDDA = Advanced Experimental Design and Data Analysis; GIS Modeling = GIS Modeling Integration for natural Resource Management; IVP = Instructional Video Production; RSHCM = Rice Seed Health for Crop Management; Intro to IRRISTAT = Introduction to IRRISTAT for Windows; G × E Analysis = Introduction to New Developments in G × E Analysis and Interpretation of Results; Analysis of Unbalanced = Analysis of Unbalanced Data; Use of IT = Use of Information Technology in Reaching Farmers; MAS = Multi-Agent Simulation Modeling for Natural Resource Management.

Communication and Publications Services Development of a time-saving, web-based information system for IRRI staff is under way. A key highlight of the system will be easy computer access to the Institute’s media assets of images and videos, selections of which were recently digitized and indexed. Plans include adding historical and classic IRRI scientific publications to the media asset mix. Training Center IRRI will assist about 130 degree and postdegree scholars and on-the-job trainees in 2001, about 50 of whom will complete their programs. Systems and procedures will be developed to increase donor support for the IRRI scholarship program, rationalize on-the-job training arrangements with sponsor agencies, and improve the administration of IRRI scholarships and management of scholars. About 25 headquarters courses will be conducted during 2001. An Experts’ Consultation in January 2001 will convene research and extension directors,

NGO leaders, IRRI country representatives, and academics to identify the training needs of their national research and extension systems. The consultation will help determine group courses to be developed and conducted by IRRI beginning in 2001. New initiatives will be applied to further strengthen IRRI’s collaborative in-country training. Collaborative in-country training activities with Thailand, Indonesia, Cambodia, and Lao PDR, will be strengthened, and activities with Korea, East Africa, and the Philippines will be initiated. Work on development of IRRI’s capability to harness new information and communication technologies for training and information delivery will be initiated. The development of IT-based courseware and online courses will be a priority activity.

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Affiliations of collaborating researchers

1Philippine 2Hokkaido

Rice Research Institute, Philippines. University, Japan. 3Assam Agricultural University, India. 4Research Institute for Rice, Indonesia. 5Central Research Institute for Food Crops, Indonesia. 6Indian Agricultural Research Institute, India. 7G.B. Pant University of Agriculture and Technology, India. 8Natural Resources Institute, UK. 9University of Aarhus, Denmark. 10Institute of Agricultural Sciences, Vietnam. 11Narendra Deva University of Agriculture and Technology, India. 12China National Rice Research Institute, China. 13Central Rice Research Institute, India. 14Punjab Agricultural University, India. 15Research Institute for Food Crop Biotechnology, Indonesia. 16Yunnan Agricultural University, China. 17Zhejiang Academy of Agricultural Sciences, China. 18Indian Institute of Soil Science, India. 19Chinese Academy of Agricultural Sciences, China. 20Bangladesh Rice Research Institute, Bangladesh. 21Malaysian Agricultural Research and Development Institute, Malaysia. 22Cuu Long Delta Rice Research Institute, Vietnam. 23Sichuan Academy of Agricultural Sciences, China. 24Indira Gandhi Agricultural University, India. 25Mariano Marcos State University, Philippines. 26Orissa University of Agricultural Technology, India. 27Rajendra Agricultural University, India. 28University of Adelaide, Australia. 29Zhejiang Agricultural University, China. 30Huazhong Agricultural University, China. 31Williams College, USA. 32Indian Institute of Science, Center for Genetic Engineering, India. 33Murugappa Chettiar Research Center, India. 34Universitat Bremen, Germany. 35University of the Philippines Diliman, Philippines. 36Banaras Hindu University, India. 37Michigan State University, USA. 38Australian National University, Australia. 39Sakha Agricultural Research Station, Egypt. 40Myanmar Agricultural Service, Myanmar. 41M.S. Swaminathan Research Foundation, India.

128

IRRI program report for 2000

Research support services
Analytical Service Laboratories 130 Biometrics 132 Communication support 133 Computer Services 133 Experiment Station 134

130

Publications and seminars
Institute publications 137 Rice research seminars 151 Division seminars 152

137

Staff changes Finances
161

155

Weather summary

162

Research support services

ANALYTICAL SERVICE LABORATORIES

The Analytical Service Laboratories (ASL) provides routine analytical and analysis-related services to IRRI research programs and special projects. ASL completed 36,723 routine analyses (Table 1). More than 500 samples for multi-element analysis were not done due to the institute’s inability to purchase nitric acid during the last quarter of the year. Training Training in safe handling of radioisotopes, particularly 32P, 33P, and 14C, was given for 13 scholars and staff members from the Molecular Biology Laboratory, the Tissue Culture Laboratory, the Gene Mapping Laboratory, and Plant Physiology. The 5-day course included review of the principles of radioactivity and radioactive decay, biological effects of radiation, basic principles and concept of radiation protection, and radiation detection instruments. Environmental considerations in the use of radioisotopes, radioisotope handling procedures and safe transport, contamination and decontamination, waste management, and licensing procedures were also covered.

Practical liquid chromatography training was given for IRRI researchers and scholars who needed to apply liquid chromatography in their research work but lacked background and training to operate high-performance liquid chromatography (HPLC). The course covered separation and equipment basics, method development, practical and important considerations, and hands-on work suited to the participant’s need. HPLC will be used to develop procedures for the determination of amino acids, phenolics and other aromatic compounds, cytokinin, sugar phosphates, photosynthetic pigments such as carotenoids, and vitamin A. User Laboratory ASL continued to provide liaison services with the Philippine Nuclear Research Institute for researchers using radiotracers in their work. Research on ion diffusion in flooded soil using 36Cl was conducted in the radioisotope laboratory facilities in the Hemmi Building. The balance of radiotracer work was done in several IRRI laboratories—Gene Mapping Laboratory, Tissue Culture Laboratory, and Molecular Biology Laboratory.

Table 1. Analyses completed by ASL for IRRI programs during 2000. Program served (no. of analyses) Service Training Irrigated Rainfed Upland Flood-prone Cross ecosystems 899 25 5 60 989 Accelerating impact 2,236 243 7 3,003 Other

Plant analysis Soil analysis Water analysis Mass spectrometry Radioisotope counting Total

26 411 270 136 1,971 2,814

7,809 2,469 5 621 115 11,019

2,751 542 243

6,262 85 7 28 6,382

0 26 2

3,536

28

5,892 472 72 545 1,971 8,952

130

IRRI program report for 2000

Organic Analysis Laboratory Two projects made use of the Organic Analysis Laboratory. Analysis of soil organic matter. Previous investigations on sustainability of intensive lowland rice cropping have demonstrated that a primary change in soil properties occurring during intensive cropping has been an accumulation of phenolic compounds in soil organic matter. Because phenols stabilize N, their accumulation in soil represents a plausible explanation for the decrease in availability of organic bound N that has been associated with long-term intensive cropping. Tetramethylammonium hydroxide (TMAH) thermochemolysis complements the previously reported pyrolysis-gas chromatography (GC)-mass spectrometry method for soil organic matter characterization (Program Report for 1998). TMAH was developed to provide faster and less expensive routine analysis of phenolic compounds in numerous humic acid samples extracted from different rice soils. Thermochemolysis involves the breakdown of organic macromolecules, such as humic acids, into smaller fragments by reaction with 25% TMAH in methanol at elevated temperature (250 oC). Methylated derivatives are then analyzed by GC (Hewlett Packard 5890 Series II Plus GC equipped with an autoinjector, an electronic pressure control, and a flame ionization detector). A few representative samples were then analyzed with a Hewlett Packard 5890 GC attached to a 5970 mass spectrometer detector to confirm the identity of the phenolic compounds. The precision of TMAH was adequate to demonstrate several trends in the phenol content of a young organic matter fraction—mobile humic acids in soil from a rice-rice rotation. q Phenol content was greater in a rice-rice rotation than from a rice-maize rotation. q During 3 years of the rice-rice rotation, the phenol content of the mobile humic acids (MHA) gradually became greater when crop residues were incorporated shortly before transplanting in anaerobic soil (traditional practice) than when incorporated in aerobic soil during the preceding fallow. q This difference was accentuated at optimal fertilizer levels.

The phenol concentration of the MHA decreased from early season to late season following anaerobic decomposition. q The late-season phenol concentration of the MHA was negatively correlated with the amount of N released from the MHA during the cropping period. Residue incorporation effects on phenol concentration and N release were agronomically significant, altering release of MHA-bound N by as much as 22 kg ha–1. Long-term water and straw management. This research seeks to identify and assess the physicochemical mechanism underlying the interaction between soil aeration and soil processes in an intensive rice system. The work will also help elucidate long-term effects of water and straw management on soil properties, rice growth, and sustainability of rice production. Part of this research project involves the study of the seasonal dynamics of root toxins. Analysis of amino acids, phenolic acids, and other low-molecular-weight organic acids in soil solutions collected from irrigated rice fields was done during the cropping season. The PICOTAG Amino Acid Analysis System (Waters Corp) was used for analysis of free amino acids. The method involved the derivatization of the sample with phenylisothiocyanate (PITC), which reacts with the amine group of amino acids to produce phenylthiocarbamyl (PTC) amino acids. These amino acid derivatives were analyzed by reversephase HPLC using PicoTag column (C18) and 481 UV detector at 254 nm. The HPLC method was slightly modified to separate only the amino acids of interest: glutamic acid, aspartic acid, asparagine, glycine, serine, L-alanine, and threonine. A method described in the Journal of Chromatography (258, 1983. 111-124) was modified for the analysis of the phenolic acids: p-hydrobenzoic, vanillic, coumaric, ferulic, sinapic, salicylic, and cinnamic. Separation was done with a Supelcosil LC-18 (15 cm × 4.6 mm, 3 µm) column heated at 35 °C with gradient mixtures of 5% formic acid and methanol as eluants. A Waters 2487 UV absorbance detector set at 280 nm was used to detect the eluted phenolic acids.
q

Research support services

131

The effects of pH, exposure to light, and presence of Fe ions on the analysis of phenolic acids were also investigated as an adjunct to the study to help in modifying and improving sampling techniques to avoid misinterpretation of data.
BIOMETRICS

The Biometrics Unit performed its traditional functions of statistical consulting, training, and biometrical research and continued development of statistical and database software. The major development was establishment of a Bioinformatics section, which will work in functional genomics and molecular breeding and provide a consulting service for bioinformatics problems. Statistical consultation The biometrics group regularly assists with the design and analysis of trials and surveys. We assisted with the analysis of multi-site trials and in the design of multi-environment evaluation trials for northeast Thailand. Collaborators from India, Bangladesh, Thailand, and Indonesia visited Biometrics and Bioinformatics for assistance with analysis and interpretation of research results. Projects the Biometrics staff were involved in during the year included q Assessment of the impact of the adoption of mixture planting for biodiversity: impact on pest management and farmers’ income (Social Sciences) q Analysis of Zn deficiency tolerance in rices in the IRRI problem-soil germplasm database (Soil and Water Sciences) q Control of planthoppers and leafhoppers in rice by the spider Atypena formosana (Entomology and Plant Pathology) q Genotype × environment (G×E) interaction analysis of rice blast nursery data in Korea Biometrics training Biometrics and Bioinformatics conducted eight courses on agricultural statistics (Table 2). Biometrics research Biometrics for analysis of G×E interactions. Pattern analysis methodologies adapted for the analysis of G×E interaction in rainfed lowland rice were used

to develop understanding at regional G×E levels in northeastern Thailand, India, Bangladesh, Indonesia, and Philippines, and, on a larger scale, across all countries. This work, in close collaboration with the Rainfed Lowland Rice Research Consortium, will continue with a second phase wherein reference genotypes will be used to characterize rainfed lowland environments through numerous small trials. This work will ultimately help focus rainfed lowland breeding efforts and to identify new traits for the development of stress-tolerant varieties. Grain quality surveys. Biometrics was involved in the IRRI-National Food Authority project on quality of milled rice in the Philippines. It had two survey components: q A survey of rice retailers to assess the Philippine Grains Standardization Program (PGSP). This also indicates consumers’ preferences for rice based on the volumes of rice sold at the retail outlets. q The collection and analysis of rice samples sold at those retail outlets to determine if they conform to PGSP standards. Database development and deployment International Rice Information System (IRIS). IRIS is fully functional for managing germplasm enahancement and evaluation data. Biometrics was involved in developing methodologies for data mining to answer questions about tolerance of germplasm for different soil streses. The work, in collaboration with the Soil and Water Sciences Division, used historical soil stress evaluation data in IRIS. A prototype web interface for IRIS was developed and will be published in 2001. A specialist

Table 2. Courses conducted by Biometrics and Bioinformatics during 2000. Course title Participants (no.) 23 18 15 16 14 24 19 5 134

Basic experimental design and data analysis Introduction to SAS for Windows (20-24 Mar) Advanced experimental designs (27-31 Mar) Cluster analysis (8-12 May) Principal component analysis (15-19 May) Introduction to IRRISTAT for Windows (14-18 Aug) Introduction to GxE analysis (21-25 Aug) Analysis of unbalanced data (11-15 Sep) Total

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web page for the IR64 mutant database was also created. Information on about 200 mutants is in the database. It is queried using the rice plant image and a treelike trait list. IRRISTAT development The IRRISTAT statistical package for Windows was improved during the year with the addition of graphics facilities for the presentation of the analysis of G×E interactions. Several improvements were made to the interface and ease of use of the software, and IRRISTAT is available as an IRRI publication for a nominal cost, or at no cost, by FTP download from the IRRI web site. Bioinformatics Bioinformatics, new for 2000, is concerned with all aspects of biological information acquisition, processing, storage, distribution, analysis, and interpretation. It combines the tools and techniques of mathematics, computer science, and biology and aims to distill biological knowledge from a variety of data sources. IRRI’s overall objective in bioinformatics is to manage and share high-quality, integrated, and relevant data analysis and interpretation with NARS and other partners and to globally publish relevant and interesting data on all aspects of rice science. A joint project between IRRI, CIAT, CIP, CIMMYT, and NCGR was developed for the integration of ICIS with comparative mapping tools being developed by NCGR. This project has a larger overall objective of assessing the opportunity for CGIAR centers to collaborate in the area of bioinformatics for comparative genomics and to center this collaboration on NCGR. Significant progress was made with the establishment of a Bioinformatics group. Efforts will be concentrated on functional genomics and molecular breeding, making sure that advanced bioinformatic tools and advice are available to IRRI researchers and collaborators.
COMMUNICATION SUPPORT

The unit printed 2,122,969 pages of text, not including IRRI books, which were contracted out. About 8,415 original slides were produced; 906 slides duplicated; and 7,351 black-and-white photographs printed. IRRI graphic artists produced 396 illustrations, laid out 1,880 pages for publication, and prepared 112 posters. Other activities are reported in Accelerating the Impact of Rice Research Program. In addition to the work reported there, IRRI editors worked on 193 journal articles and miscellaneous papers (conference papers, proposals, posters, abstracts, and others) totaling about 4,305 pages of text, tables, and figures.

COMPUTER SERVICES

Infrastructure Two new CISCO 3640 routers give IRRI a highspeed Internet connection to PHNET, a national research and education network. PHNET, based in Makati, Philippines, is a member of the Asia Pacific Advanced Network (www.apan.net), which IRRI has used for video conferencing in the region. When IRRI got its fulltime Internet link in 1995, a link to the United States was the best option. The Internet has changed dramatically since then and a local connection is by far the best option. Tenders were issued for replacement of the integrated voice and data network. Although IRRI will move to a local Internet link in 2001, the current leased line to the United States will be retained for voice communications on a lower capacity circuit. IRRI will thus retain free calls between CGIAR centers, for U.S. phone numbers for incoming calls and faxes, and access to U.S. toll-free numbers. Software development All IRRI-developed applications survived the Y2K problem. A special Y2K task force was set up by Computer Services and all affected systems were retired or replaced. Only one application had problems after 2000 and it was not related to Y2K. Sourcing a project management solution from another center. IRRI started running project manager software provided by CIAT, through the efforts of a CIAT staff member who visited IRRI. CIAT’s willingness to share the software application saved IRRI from having to create software already in ex-

The Communication and Publications Services (CPS) provides communication support for the entire institute. The services include editing, graphic design, art and illustration, audio-visual, photography, video, and printing.

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istence. The CIAT staff member returned to CIAT with shared IRRI-developed applications. The IRRI director general sent thanks to CIAT for its willingness to share their project management application with the rest of the CGIAR system, citing it as tangible evidence of a new spirit of cooperation in the system. Services Better bandwidth management. Computer Services introduced new software to regulate the use of the institute’s Internet connection by blocking undesirable sites. A lot of IRRI’s bandwidth was being dissipated by screensavers, and the like, users of which had no idea that their use was having an adverse impact on the usability of the net. Introduction of network attached storage devices. Most of IRRI’s digital information has been held on the hard disks of individual PCs. Computer Services introduced low-cost network storage systems designed to begin the process of migrating information from PCs to the IRRI network, where it will be backed up regularly, and where it can be accessed from other computers. That will eventually include those in the homes of IRRI scientists. Policy IRRI’s organizational units have ventured into web publishing more or less independently, with the result that IRRI’s Intranet is scattered over many servers throughout the institute. Computer Services reached an agreement with CPS to consolidate IRRI’s Intranet on systems managed in the CPS building, which Computer Services now shares with CPS. Other divisions will be persuaded to let Computer Services host their information centrally. This will facilitate storage management—making backups and offline copies of information (e.g., on CDROM) for dissemination to NARS and other partners.
EXPERIMENT STATION

structed with a modified tractor-powered rototiller with a flutted roller to mark rows as furrows. Work started on development of a wetbed maker attached to the 4-wheel tractor for lowland wet soil to prepare wetbeds. We expect a reduction of labor to about 50% in the wetbed nursery preparation. Almost 70 t of fertilizer materials were applied during the year. ES planted and harvested 19.7 ha of lowland fields for breeder seed increase and seed production. Crop establishment in seed production plots was mechanized using a mechanical transplanter, a backpack seed blower-spreader, or direct seeding. The Thai combine harvester was used to harvest and thresh seed production plots and borders of experimental plots, but it got minimal use during WS due to mobility problems in deeper fields. A total of 163 t of different rice materials were processed (threshing, drying, cleaning, storing) from harvests of seed increase, seed production, and border rows of experimental plots. Plant Breeding, Genetics and Biochemistry (PBGB), which occupies 60% of the requested area, increased field planting by almost 32%. Integrated pest management (IPM) was practiced in some of the seed increase and seed production areas. Insecticide use increased by 10% and molluscicide use by 88% over 1999 levels, mainly due to an increase in area planted. However, herbicide use was reduced by 36% due to limited applications because of prevalence of rainfall during the year. Pesticide applicator exposures to agrochemicals continue to be reduced with the use of mechanized equipment. ES provided rat control services consisting of 2,275 baiting stations installed with 1,550 kg of rat
Table 3. Support provided to IRRI research divisions by the Experiment Station during 2000. Division Dry season (ha) 70.04 15.28 16.80 11.30 4.00 6.56 4.68 0.51 129.17 Wet season (ha) 74.95 3.89 11.11 8.36 4.00 5.43 1.36 109.10

The Experiment Station (ES) served 226 requests for land and facilities and provided support on 238 ha of fields (Table 3). Nursery requirements for 2000 totaled 7.19 ha (3 ha drybed and 4.19 ha wetbed) provided and maintained by the station staff. The drybeds were con-

Plant Breeding, Genetics, and Biochemistry Genetic Resources Center Soil and Water Sciences Experiment Station CIAT Entomology and Plant Pathology Agricultural Engineering Training Center Total

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baits for research station and outreach areas. In addition, active barrier system fences for 95.92 ha, with 1,038 live traps, were installed. Nearly 5,000 rats were caught during the year. About 5,626 m2 of bird nets were also installed. Improvement in the irrigation system continued with the installation of polyvinyl chloride irrigation pipes in Block G11, UM and UN, and installation of cement pipes at Series 600. An additional 64 manholes were installed at Blocks E, G11, M8, N, UB, UC, UE, UF, UG, UL, UN, UQ, UR, UU, UV, U, and Series 200, 300, 600. Drainage outlets were developed and constructed in Blocks G11, UE, UF, UG, UU, UV, UY, and Series 600. Drainage rehabilitation work continued at Blocks B2, UJ, UN, and UQ. Underground pipes were lowered or slopes improved. Land development work consisted of conversion of upland to lowland fields in the whole block of UD (4 ha) to provide additional area for GRC nurseries and other uses. Major road rehabilitation and repair work were done in Block A, Road 26 North, screenhouse roads, and the main road of old lowland and upland areas. Backfilling and reshaping of plots beside 500 reservoir and the entrance of IRRI (beside the railroad) were completed. Controlled growth facilities and grounds The Controlled Growth Facilities and Grounds (CGFG) Unit supported a total of 34 experiments in the phytotron, 140 experiments in greenhouses, and more than 16 experiments in the confinement level 4 (CL4) transgenic greenhouses. A total of 3,261 maintenance service requests were served, which included provision of 875 t of ground soil to various experiments in the greenhouses and fields. The annual shutdown of the phytotron started 15 d earlier than the customary December shutdown. Servicing of the various facilities was staggered over a 45-d period to facilitate earlier scheduling of experiments by researchers before 2001, help reduce work peaks and holiday rush that typically occur every December, and avoid overtime costs associated with holidays. Thirty-two type-M solar panels were installed as part of the gradual replacement program for the old model solar panels of the phytotron solar heating system. Replacement of all old panels will be com-

pleted in 2001. Worn-out insulation on the hot water lines and air-handling units of the glasshouse bays were replaced. The pressure tank that services the growth cabinets was replaced with a more suitable and reliable unit. New hermetic and semi-hermetic compressors were acquired as part of the replacement program for the chillers servicing the phytotron cooling system. Polyvinyl pipes were installed in the roof gutters of the phytotron building to collect rainwater in an existing concrete tank. This augments the rainwater supplied by the underground rainwater collecting tank that services the humidification and cooling systems of the growth chambers. The two rainwater tanks combined help the phytotron save the use of more than 400,000 L of demineralized water annually. This system, in combination with the reverse osmosis water supply pipe connection of the phytotron to the Umali Laboratory, replaced inefficient electric boiler and demineralizer units. Power consumption of the phytotron for the year was 167,200 kwh lower than for 1999. Compared with 1989 and 1990 levels (2,738,400 kwh at $139,795 and 2,523,200 kwh at $123,329), the current power consumption represents 41–46% reduction. This translates to US$71,000–87,800 annual power-cost savings attributed to modernization and improved systems at the phytotron. Greenhouse Unit The Greenhouse Unit maintained 44 glasshouse and screenhouse structures and provided a wide range of services to facilitate experiments in them. Soil grinding and hauling remained a main bulk of daily operations. An increase over 1999 of about 175 t pulverized soil for greenhouse and field experiments was noted. The greenhouse crew accomplished a one-month preventive shutdown for 24 greenhouses on a staggered schedule, which allowed servicing of at least two greenhouses each month. Shutdown services included general cleanup and surface washdown of all the structures and provisions for prophylactic chemical treatment against pests. Preventive maintenance of cooling systems and structures was also done. The shutdown operations as standard procedure in all greenhouses are primarily aimed to disrupt insect and disease cycles and reduce the frequency of chemical spraying against pests. It is also

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a proactive approach to maintenance of machinery and structures in the greenhouses. Some 200 m2 of the Entomology and Plant Pathology Division’s plant-growing and insect-rearing areas were concrete paved to reduce ground maintenance costs, improve aesthetics, and facilitate staff access to experimental setups. A new higher capacity soil heat sterilizer was acquired to meet increasing demand for soil sterilization. The headhouse at cluster N, razed by fire in 1999, was fully restored and is back to normal operation. Asbestos roofing of another headhouse at cluster M was replaced with standard metalplas roof sheets. Improvements in the upland screenhouse complex include installation of steel covers for the drainage, repainting of support structures, replacement of screen walls, and reinstallation of the misting system for the maintenance of some wild rice species. Light transmission of metalplas greenhouse roofing was measured at only 70% compared with glass with light transmissions reaching as high as 90%. Agronomic lamps were installed in one metalplascovered greenhouse to augment light levels during periods of limited sunlight. The lamps were found to increase light levels up by as much as 20% but with an associated increase in temperature at the plant canopy level by 1 to 2 °C. A new polycarbonate roofing material, with light transmission of 90%, was installed in a greenhouse and is being tested. The new material is fire retardant, lighter, less fragile, cheaper, and safer to use than glass. Grounds Unit The Grounds Unit provided landscape maintenance and development services, including garbage collection, to the main research center and to 104 residential units and common areas of staff housing and IRRI-rented apartments.

Road widening was done at the entrance to the parking area of grounds equipment near the phytotron to improve safety and facilitate the maneuver of heavy equipment. Old hedges around the F.F. Hill, Umali Laboratory, and Physical Plant buildings were removed and replaced as appropriate. Seven-year-old coconut trees were cut down for safety considerations and trimming of trees was done in some communal areas to help avoid potential accidents due to broken tree branches during windy days. Implementation of the waste segregation and recycling program continued generating funds through periodic sales of recyclable wastes via public auction and has caught the attention of various groups and organizations taking interest on waste management. IRRI staff have been invited on several occasions to share information and expertise on the topic. Two hundred and fifty plant identification labels were installed on different plant species in the staff housing, guesthouse, and some communal areas. Five seedlings of the rare vine Mucuna benettii were successfully propagated this year as a result of previous joint efforts between the Makiling Botanic Gardens, Institute of Forest Conservation, and the IRRI Grounds Unit to develop macro-propagation techniques that will help conserve the species. Additional improvements to IRRI’s grounds include the construction of a new passageway and bridge as well as a new parking lot near the IRRI main gate to improve traffic flow of people and vehicles visiting the IRRI Riceworld Museum. Grounds development was also initiated along the concrete paved road leading to the staff housing and along the perimeter fence of the IRRI main entrance gate in coordination with UPLB staff.

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Publications and seminars

Institute publications
Books Rice tungro disease management. 2000. 166 p. IRRI 1999-2000: the rewards of rice research. 2000. 72 p. The quest for nitrogen fixation in rice. 2000. 354 p. Systems research for optimizing future land use in South and Southeast Asia. 1999. 266 p. Program report for 1999. 2000. 175 p. Carbon and nitrogen dynamics in flooded soils. 2000. 188 p. Redesigning rice photosynthesis to increase yield. 2000. 293 p. Characterizing and understanding rainfed environments. 2000. 488 p. Periodicals/serials International rice research notes, vol. 25, nos. 1-3. IRRI discussion paper series, Nos. 38-41. IRRI limited proceedings series, Nos. 2-5. Agricultural Engineering Alam M, Bell MA, Mortimer AM, Hussain MD, Bakker RR, Castro EC Jr, Razote EB. 2000. Pesticide application techniques of rice farmers in the Philippines and options to improve application and protect the environment. In: Proceedings of the 14th Memorial CIGR World Congress, 28 Nov-1 Dec 2000, Tsukuba, Japan. p 29-35. Bakker RR, Bell MA, de Padua DB. 1999. Targeting the needs of producers and consumers in rice post-production systems research. In: Proceedings of the GASGA Seminar 11—The Importance of PostProduction to Sustainable Rural Livelihoods,

23-24 Jun 1999, Natural Resources Institute, Chatham, UK. p 66-70. Bakker RR, Rickman JF, Bell MA. 2000. Improving productivity in direct-seeded rice: the rule of mechanization. In: Proceedings of the 14th Memorial CIGR World Congress, 28 Nov-1 Dec 2000, Tsukuba, Japan. Bell MA, Bakker RR, de Padua DB, Rickman J. 1999. Rice quality management—principles and some lessons. In: Quality assurance in agricultural produce. ACIAR proceedings no. 100. Proceedings of the 19th ASEAN/1st APEC Seminar on Postharvest Technology, 9-12 Nov 1999, Ho Chi Minh City, Vietnam. p 255-263. Borlagdan PC. 2000. Evaluation and adaptive modification of a low-cost paddy drying technology. Philipp. Eng. J. 21(2):42-52. De Padua DB. 1999. The Philippine rice postproduction consortium needs assessment of the postproduction industry. In: Quality assurance in agricultural produce. ACIAR proceedings no. 100. Proceedings of the 19th ASEAN/1st APEC Seminar on Postharvest Technology, 912 Nov 1999, Ho Chi Minh City, Vietnam. p 398-407. Hammen VC, Bell MA, Castro EC Jr, Bakker RR. 2000. Nondestructive on-line sensing of rice crop biomass. In: Proceedings of the 14th Memorial CIGR World Congress, 28 Nov-1 Dec 2000, Tsukuba, Japan. p 1046-1051. Rickman JF, Bunna S, Sinath P, Pyseth M. 1999. Rice milling in Cambodia. In: Quality assurance in agricultural produce. ACIAR proceedings no. 100. Proceedings of the 19th ASEAN/1 st APEC Seminar on Postharvest Technology, 9-12 Nov 1999, Ho Chi Minh City, Vietnam. p 520-522.

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Crop, Soil, and Water Sciences Aggarwal PK, Kalra N, Kumar S, Pathak H, Bandyopadhyay SK, Vasisht AK, Roetter RP, Hoanh CT. 2000. Haryana State case study: trade-off between cereal production and environmental impact. In: Roetter RP, Van Keulen H, Van Laar HH, editors. Synthesis of methodology development and case studies. SYSNET Res. Pap. Ser. 3. Alam M, Bell MA, Mortimer AM, Hussain MD, Bakker RR, Castro EC Jr, Razote EB. 2000. See Agricultural Engineering. Amarante ST, Olea A, Harnpichitvitaya D, Naklang K, Wihardjaka A, Sengar SS, Mazid MA, Singh G, McLaren CG, Nieuwenhuis P, Wade LJ. 2000. Recent nutrient research on rainfed lowland rice with emphasis on nutrient by water interactions. Philipp. J. Crop Sci. 25:72. Arah JRM, Kirk GJD. 2000. Modelling rice plantmediated methane emission. Nutr. Cycl. Agroecosyst. 58:221-230. Azhiri-Sigari T, Gines H, Sebastian L, Wade LJ. 2000. Seedling vigor of direct seeded rice cultivars in response to seeding depth and planting method. Philipp. J. Crop Sci. 25:19. Azhiri-Sigari T, Yamauchi A, Kamoshita A, Wade LJ. 2000. Genotypic variation in response of rainfed lowland rice to drought and rewatering. 2. Root growth. Plant Prod. Sci. 3:180-188. Bal P, Castella JC, Le Quoc Doanh, Husson O, Tran Dinh Long, Dang Dinh Quang, Ha Dinh Tuan, Duong Duc Vinh. 2000. Diagnostic systémique, recherche agronomique et appui au développement: exemple d’une intervention concertée dans la province de Bac Kan [in French and Vietnamese]. In: Appui à l’organisation de la production agricole dans le Nord du Vietnam, Maison d’edition de l’Agriculture, Hanoi, Vietnam. p 57-92. Banoc DM, Yamauchi, A Kamoshita A, Wade LJ, Pardales JR. 2000. Dry matter production and root system development of rice cultivars under soil moisture fluctuations. Plant Prod. Sci. 3:197-207. Banoc DM, Yamauchi A, Kamoshita A, Wade LJ, Pardales JR. 2000. Genotypic variations in response of lateral root development to fluctuating soil moisture. Plant Prod. Sci. 3:335-343.

Bessembinder J, van Ittersum MK, Schipper RA, Bouman BAM, Hengsdijk H, Nieuwenhuyse A. 2000. Exploring future land use options: combining biophysical considerations and societal objectives. In: Bouman BAM, Jansen HGP, Schipper RA, Hengsdijk H, Nieuwenhuyse A, editors. Tools for land use analysis on different scales; with case studies for Costa Rica. Dordrecht (The Netherlands): Kluwer Academic Publishers. p 145-170. Bird JA, Horwath WR, van Kessel C, Hill JE. 1999. Effect of flooding and straw residue management on soil bulk density in two flooded Vertisols: implications for nutrient cycling research. ASA-CSSA-SSSA Annual Meeting Abstracts, Salt Lake City, Utah, 31 October-4 November. p 237. Biswas JC, Ladha JK, Dazzo FB. 2000. Rhizobial inoculation improves nutrient uptake and growth of lowland rice. Soil Sci. Soc. Am. J. 64:1644-1650. Biswas JC, Ladha JK, Dazzo FB, Yanni YG, Rolfe BG. 2000. Rhizobial inoculation influences seedling vigor and yield of rice. Agron. J. 92:880-886. Bouma J, Jansen HGP, Kuyvenhoven A, van Ittersum MK, Bouman BAM. 2000. Introduction. In: Bouman BAM, Jansen HGP, Schipper RA, Hengsdijk H, Nieuwenhuyse A, editors. Tools for land use analysis on different scales; with case studies for Costa Rica. Dordrecht (The Netherlands): Kluwer Academic Publishers. p 1-8. Bouman BAM, Jansen HGP, Schipper RA, Bouma J, Kuyvenhoven A, van Ittersum MK. 2000. A toolbox for land use analysis. In: Bouman BAM, Jansen HGP, Schipper RA, Hengsdijk H, Nieuwenhuyse A, editors. Tools for land use analysis on different scales; with case studies for Costa Rica. Dordrecht (The Netherlands): Kluwer Academic Publishers. p 213-232. Bouman BAM, Jansen HGP, Schipper RA, Hengsdijk H, Nieuwenhuyse A, editors. 2000. Tools for land use analysis on different scales; with case studies for Costa Rica., Dordrecht (The Netherlands): Kluwer Academic Publishers. p. 274 Bouman BAM, Tuong TP. 2000. Field water management and increasing productivity in

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irrigated rice. Agric. Water Manage. 1615:120. Bulte EH, Bouman BAM, Plant RAJ, Nieuwenhuyse A, Jansen HGP. 2000. The economics of soil nutrient stocks and cattle ranching in the tropics: optimal pasture degradation in humid Costa Rica. Eur. Rev. Agric. Econ. 27(2):207-226. Buresh RJ, Dobermann A, Belleza E, Padilla JL. 2000. Nutrient dynamics and availability during long-term continuous cropping of lowland rice. ASA-CSSA-SSSA 2000 Annual Meeting Abstracts, 5-9 November 2000, Minneapolis, MN, ASA-CSSA-SSSA, Madison, WI. p 280. Buresh RJ, Ladha JK, Dobermann A, Jr Pascua SR, Padre AT, Aduna J, Obien SR. 2000. Soil carbon and nitrogen changes in intensive ricebased cropping systems. ASA-CSSA-SSSA 2000 Annual Meeting Abstracts, 5-9 November 2000, Minneapolis, MN, ASACSSA-SSSA, Madison, WI. p. 253. Cabangon RJ, Tuong TP. 2000. Soil management for water saving during land preparation of cracked rice soils. Soil Till. Res. 56:105-116. Caton BP, Hill JE, LeStrange M, Cavero J. 1999. Response surface analysis of nitrogen rate effects on competition between water-seeded rice and Echinochloa oryzoides (Ard.) Fritsch. Third International Weed Science Congress (IWSC) Abstracts, Foz Do Iguaçu, Brazil, 6-11 June. p 76. Centeno HGS, Dawe DD, Hammer GL, Sheehy JE. 2000. Impacts of ENSO on rice yields in Asia. In: Linking science to society. Proceedings of the International Forum on Climate Prediction, Agriculture, and Development, 26-28 April 2000, Palisades. New York. Charrel H, Tomsett AB, Mortimer M, Kemp S. 2000. A molecular analysisof weedy rice from the Philippines. XXIIeme Reunion Annuelle du Groupe de Biologie et Genetique des Populations. Dijon (France): INRA. p 43-45. Charrel H, Tomsett AB, Mortimer M, Kemp S. 2000. Approaches to the molecular ecology of weedy rice in Southeast Asia. In: Proceedings of the 44th Annual Meeting of the Ecological Genetics Group. UK: British Ecological Society. p 85-86.

Dawe D, Dobermann A, Moya P, Abdulrachman S, Bijay Singh, Lal P, Li SY, Lin B, Panaullah G, Sariam O, Singh Y, Swarup A, Tan PS, Zhen QX. 2000. See Social Sciences. De Luna LZ, Watson AK, Paulitz TC. 2000. Seedling blight of Cyperaceae weeds caused by Curvularia tuberculata and C. oryzae. Abstracts. 2000 Meeting of the Weed Science Society of America, Toronto. Dey M, Datta SK, Torrizo LB, Reddy PM, Ladha JK, Day B, Stacey G. 1999. Integration into rice of a soybean apyrase gene proposed to play a central role in nodulation. Rice Genet. Newsl. 16:145-147. Dey M, Torrizo LB, Chaudhuri RK, Reddy PM, Ladha JK, Datta K, Datta SK. 1999. Transgenic rice harboring legume ENOD40 gene. Rice Genet. Newsl. 16:147-149. Dizon M, Piggin C, Mortimer AM, Lubigan R, Hill JE, Namuco OS, Migo T. 1999. Effect of afterripening temperature on seed germination of Echinochloa crus-galli (L.) Beauv. Third International Weed Science Congress (IWSC) Abstracts, Foz Do Iguaçu, Brazil, 6-11 June. p 24. Dobermann A, Dawe D, Roetter RP, Cassman KG. 2000. Reversal of rice yield decline in a longterm continuous cropping experiment. Agron. J. 92:633-643. Eagle AJ, Bird JA, Horwath WR, Lindquist BA, Brouder SM, Hill JE, van Kessel C. 2000. Rice yield and nitrogen utilization efficiency under alternative straw management practices. Agron. J. 92:1096-1103. Eagle AJ, van Kessel C, Horwath WR, Bird JA, Hill JE. 1999. Nitrogen cycling dynamics under alternative rice straw management practices. ASA-CSSA-SSSA Annual Meeting Abstracts, Salt Lake City, Utah, 31 October-4 November. p 220. Eusebio AA, Watson AK. 2000. Mixtures of fungal pathogens to control complex weeds of weeds in rice. Abstracts. Third International Weed Science Congress, 6-11 June 2000, Foz do Iguaçu, Brazil. p 153. Fischer AJ, Ateh CM, Bayer DE, Hill JE. 2000. Herbicide-resistant Echinochloa oryzoides and E. phyllopogon in California Oryza sativa fields. Weed Sci. 48:225-230.

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Fitzgerald GJ, Scow KM, Hill JE. 2000. Fallow season straw and water management effects on methane emissions in California rice. Global Biogeochem. Cycl. (14)3:767-776. Gathumbi SM, Ndufa JK, Giller KE, Buresh RJ, Cadisch G. 2000. Mixed species fallows: complementarity or competition in growth resource utilization. ASA-CSSA-SSSA 2000 Annual Meeting Abstracts, 5-9 November 2000, Minneapolis, MN. Madison (WI): ASACSSA-SSSA. p 60. George T, Magbanua R, Tubana B, Quiton J, Almendras A, Khatib W, Cox F, Yost R. 2000. Estimating buffer coefficients for the phosphorus decision support system using field and laboratory measurements. Comm. Soil Sci. Plant Anal. 31:2101-2110. George T, Quiton J, Yost R. 2000. Determining critical soil phosphorus levels for upland crops. ASA-CSSA-SSSA 2000 Annual Meeting Abstracts, 5-9 November 2000, Minneapolis, MN. Madison (WI): ASA-CSSA-SSSA. Gibson KD, Foin TC, Hill JE. The relative importance of root and shoot competition between water-seeded rice and watergrass. Weed Res. 39:181-190. Gyaneshwar P, Reddy PM, Ladha JK. 2000. Nutrient amendments influence endophytic colonization of rice by Serratia marcescens IRBG500 and Herbaspirillum seropedicae Z67. J. Microbiol. Biotechnol. 10:694-699. Hartemink AE, Buresh RJ, van Bodegom PM, Braun AR, Jama B, Janssen BH. 2000. Inorganic nitrogen dynamics in fallows and maize on an Oxisol and Alfisol in the highlands of Kenya. Geoderma 98:11–33. Hengsdijk H, Bouman BAM, Nieuwenhuyse A, Schipper RA, Bessembinder J. 2000. Technical coefficient generators for quantifying land use systems. In: Bouman BAM, Jansen HGP, Schipper RA, Hengsdijk H, Nieuwenhuyse A, editors. Tools for land use analysis on different scales; with case studies for Costa Rica. Dordrecht (The Netherlands): Kluwer Academic Publishers. p 97-14. Hill JE. 2000. Weed management: direct-seeded rice in the USA. Third International Weed Science Congress (IWSC) Abstracts. Foz Do Iguaçu, Brazil, 6-11 June. p 245.

Hoanh CT, Roetter RP, Laborte AG, Aggarwal PK, Bakar IA, Tawang A, Lansigan FP, Francisco S, Lai NX. 2000. Scenario analysis in land use planning: examples from four case studies of the SysNet project. CD-ROM Proceedings SAAD-3, CIP, Lima, Peru, Nov 8-10, 1999. Hossain M, Singh VP. 2000. See Social Sciences. Huang S, Watson AK, Duan G, Yu L. 2000. Preliminary study on three pathogens with potential biological control in barnyardgrass (Echinochloa crus-galli). China Rice Res. Newsl. 8(1):8-9. Hussain F, Bronson KF, Yadvinder-Singh, BijaySingh, Peng S. 2000. Use of chlorophyll meter sufficiency indices for nitrogen management of irrigated rice in Asia. Agron. J. 92:875-879. Jama B, Buresh RJ, Place F, Franzel S, Smithson PC. 2000. Enhancing research relevance through researcher–farmer interactions. ASACSSA-SSSA 2000 Annual Meeting Abstracts, 5-9 November 2000, Minneapolis, MN. Madison (WI): ASA-CSSA-SSSA. p 60. Jama B, Buresh RJ, Smithson PC, Mbugua PN, Smestad T, Tiessen H. 2000. Maize yields and soil phosphorus fractions following woody leguminous fallows in western Kenya. ASACSSA-SSSA 2000 Annual Meeting Abstracts, 5-9 November 2000, Minneapolis, MN. Madison (WI): ASA-CSSA-SSSA. p 59. Jama B, Palm CA, Buresh RJ, Niang A, Gachengo C, Nziguheba G, Amadalo B. 2000. Tithonia diversifolia as a green manure for soil fertility improvement in western Kenya: a review. Agrofor. Syst. 49:201–221. Jansen HGP, Schipper RA, Roebeling P, Bulte EH, Hengsdijk H, Bouman BAM, Nieuwenhuyse A. 2000. Alternative approaches to the economics of soil nutrient depletion in Costa Rica: exploratory, predictive and normative bio-economic models. In: Heerink N, van Keulen H, Kuiper M, editors. 2001. Economic policy and sustainable land use: recent advances in quantitative analysis for developing countries. Physica-Verlag: Heidelberg, New York. p 211-238. Jensen LB, Olofsdotter M, Courtois B. 2000. Genetic control of allelopathy in rice (Oryza sativa L.). In: Kim KU, editor. Proceedings of the International Workshop on Rice

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Allelopathy, Taegu, Korea, August 2000. p 2334. Jiang C, Edmeades GO, Armstead I, Lafitte HR, Hayward MD, Hoisington D. 1999. Genetic analysis of adaptation differences between highland and lowland tropical maize using molecular markers. Theor. Appl. Genet. 99:1106-1119. Kam SP, Castella JC, Hoanh CT, Trebuil G, Bousquet F. 2000. Methodological integration: lessons from the Ecoregional Initiative for the Humid and Sub-Humid Tropics of Asia. In: Proceedings of the Workshop on Integrated Natural Resources Management in the CGIAR : Approaches and Lessons, 21-25 August 2000, Penang, Malaysia. 23 p. Kam SP, Hoanh CT, Alvaran A. 2000. Area representation errors associated with rasterization. In: Heuvelink GBM, Lemmens JMPM, editors. Accuracy 2000. Proceedings of the 4th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, July 2000, Amsterdam, The Netherlands. p 337-342. Kam SP, Tuong TP, Hoanh CT, Ngoc NV, Minh VQ, 2000. Integrated analysis of changes in rice cropping systems in the Mekong River Delta, Vietnam, by using remote sensing, GIS, and hydraulic modeling. Electronic Proceedings (CD ROM) of the XIX International Congress for Photogrammetry and Remote Sensing, July 2000, Amsterdam, The Netherlands. 8 p. Kamoshita A, Wade LJ, Yamauchi A. 2000. Genotypic variation in response of rainfed lowland rice to drought and rewatering. 3. Water extraction during the drought period. Plant Prod. Sci. 3:189-196. Kinyangi JM, Smucker AJ, Harwood RR, Buresh RJ. 2000. Phosphorus availability from multiple concentric layers in soil aggregates. ASA-CSSA-SSSA 2000 Annual Meeting Abstracts, 5-9 November 2000, Minneapolis, MN. Madison (WI): ASA-CSSA-SSSA. p 289. Kondo M, Shrestha RK, de Vera Aragones D, and Ladha JK. 2000. Effect of indigo and maize as nitrogen catch crops on root growth and nitrogen use in rice in rainfed lowland ecosystems in northern Philippines. Jpn. J. Trop. Agric. 44:12-19.

Kronzucker HJ, Glass ADM, Siddiqi MY, Kirk GJD. 2000. Comparative kinetic analysis of ammonium and nitrate acquisition by tropical lowland rice: implications for rice cultivation and yield potential. New Phytol. 145:471-476. Kyu H. 2000. Manipulation of seedling vigor and the implications for performance of wet-seeded rainfed lowland rice. Ph D thesis, Department of Agronomy, University of the Philippines Los Baños, Laguna, Philippines. 231 p. Kyu H, Amarante ST, Gomez AA, Samonte HP, Robles RP, Wade LJ. 2000. Seed and seedling vigor and the implications for performance of wet-seeded rainfed lowland rice. In: Abstracts. Third International Crop Science Congress, Hamburg. p 169. Kyu H, Amarante ST, Gomez AA, Samonte HP, Robles RP, Wade LJ. 2000. Manipulating seed and seedling vigor and implications for performance of wet-seeded rainfed lowland rice. In: Abstracts. Direct seeding in Asian rice systems, Bangkok. p 25. Laborte AG, Roetter RP, Hoanh CT. 2000. The land use planning and analysis system of the systems research network in Asia. CD-ROM Proceedings, MODSS’99, 1-6 Aug 1999, Brisbane. Ladha JK, Dawe D, Ventura TS, Singh U, Ventura W, Watanabe I. 2000. Long-term effects of urea and green manure on rice yields and nitrogen balance. Soil Sci. Soc. Am. J. 64. Lafitte HR, Courtois B. 2000. Genetic variation in performance under reproductive-stage water deficit in a doubled haploid rice population in upland fields. In: Ribaut J-M, Poland D, editors. Molecular approaches for the genetic improvement of cereals for stable production in water-limited environments. A strategic planning workshop, 21-25 Jun 1999. El Batan (Mexico): CIMMYT. p 97-102. Li Z, Shen L, Courtois B, Lafitte HR. 1999. Development of near-isogenic introgression line (NIIL) sets for QTLs associated with drought tolerance in rice. In: Ribaut J-M, Poland D, editors. Molecular approaches for the genetic improvement of cereals for stable production in water-limited environments. A strategic planning workshop, 21-25 Jun 1999. El Batan (Mexico): CIMMYT. p 103-107.

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Livesley SJ, Gregory PJ, Buresh RJ. 2000. Competition in tree row agroforestry systems. 1. Distribution and dynamics of fine root length and biomass. Plant Soil 227:149–161. Mabbayad MO, Watson AK. 2000. Rejection of Fusarium pallidoroseum as a biological control agent of Mimosa invisa. Biocontr. Sci. Technol. 10:255-266. Mahieu N, Olk DC, Randall EW. 2000. Accumulation of heterocyclic nitrogen in humified organic matter: a 15N-NMR study of lowland rice soils. Eur. J. Soil Sci. 51:379-389. Mahieu N, Olk DC, Randall EW. 2000. Analysis of phosphorus in two humic acid fractions of intensively cropped lowland rice soils by 31PNMR. Eur. J. Soil Sci. 51:391-402. Masangkay RF, Paulitz TC, Hallett SG, Watson AK. 2000. Characterization of sporulation of Alternaria alternata f. sp. sphenocleae. Biocontr. Sci. Technol. 10:385-397. Masangkay RF, Paulitz PC, Watson AK. 2000. Solid substrate production of Alternaria alternata f. sp. sphenocleae conidia. Biocontr. Sci. Technol. 10:399-409. Mazid MA, Bhuiyan SI, Mannan MA, Wade LJ. 2000. Dry-seeded rice for enhancing the productivity of rainfed drought-prone lands: lessons from Bangladesh and the Philippines. In: Abstracts. Direct seeding in Asian rice systems, Bangkok. p 15-16. Ngoze SO, Buresh RJ, Okalebo JR, van Straaten P, Jama B, Smithson PC. 2000. Evaluation of fertilizer products derived from Busumbu phosphates in eastern Uganda. ASA-CSSASSSA 2000 Annual Meeting Abstracts, 5-9 November 2000, Minneapolis, MN, Madison (WI): ASA-CSSA-SSSA. p 281. Nieuwenhuyse A, Bouman BAM, Jansen HGP, Schipper RA, Alfaro R. 2000. The physical and socio-economic setting. In: Bouman BAM, Jansen HGP, Schipper RA, Hengsdijk H, Nieuwenhuyse A, editors. Tools for land use analysis on different scales; with case studies for Costa Rica. Dordrecht (The Netherlands): Kluwer Academic Publishers. p 9-34. Nieuwenhuyse A, Hengsdijk H, Bouman BAM, Schipper RA, Jansen HPG. 2000. Can forestry be a competitive land use option? Model simulations from humid tropical Costa Rica. For. Ecol. Manage. 137(1-3):23-40.

Nozoe T. 2000. Mechanisms and suppression of the accumulation of volatile fatty acids and the production of methane in submerged paddy soil. Bull. Tohoku Natl. Agric. Exp. Stn. 97:75129. Nyberg G, Ekblad A, Buresh RJ, Högberg P. 2000. Respiration from C3-plant green manure added to a C4-plant carbon dominated soil. Plant Soil 218:83–89. Oberthür T, Dobermann A, Aylward M. 2000. Using auxiliary information to adjust fuzzy membership functions for improved mapping of soil qualities. Int. J. Geogr. Inf. Syst. 14:431451. Oberthür T, Dobermann A, White PF. 2000. The rice soils of Cambodia. II. Statistical discrimination of soil properties by the Cambodian Agronomic Soil Classification System (CASC). Soil Use Manage. 16:20-26. Olk DC, Brunetti G, Senesi N. 2000. Decrease in humification of organic matter with intensified lowland rice cropping: a wet chemical and spectroscopic investigation. Soil Sci. Soc. Am. J. 64:1337-1347. Olofsdotter M. 2000. My view—why won’t breeders do what we want? Weed Sci. 48: (5):521-531. Olofsdotter M, Inderjit. 2000. Allelopathy in the agroecosystem. In: Proceedings of the American Weed Science Conference in Toronto, Canada, Feb 2000. p 124. Olofsdotter M, Jensen LB. 2000. Improving crop competitive ability using allelopathy. Book of abstracts from the Third International Crop Science Congress, Hamburg, Germany, August 2000. p 89. Olofsdotter M, Jensen LB, Navarez D, Pamplona R, Rimando A. 2000. Progress in rice allelopathy. In: Proceedings of the Third International Weed Control Congress, Foz do Iguaçu, Brazil. p 33. Olofsdotter M, Valverde B, Madsen KH. 2000. Herbicide resistant rice—a threat or a solution? Report of FAO global workshop on herbicideresistant rice, Cuba, 30 Aug-3 Sep 1999. Rome: Plant Production and Plant Protection Division, Food and Agriculture Organization. p 123-145. Osborne CP, Mitchell PL, Sheehy JE, Woodward FI. 2000. Modelling the recent historical impacts of atmospheric CO 2 and climate

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change on Mediterranean vegetation. Global Change Biol. 6:445-458. Pamplona RR, Navarez D, Mortimer AM, Olofsdotter M. 2000. Seedling recruitment of Echinochloa crus-galli in relation to rice establishment method and companion cultivar. In: Proceedings of the Third International Weed Control Congress, Foz do Iguaçu, Brazil, p 38. Peng S, Laza RC, Visperas RM, Sanico AL, Cassman KG, Khush GS. 2000. Grain yield of rice cultivars and lines developed in the Philippines since 1966. Crop Sci. 40:307-314. Ram S, Chauhan RPS, Singh BB, Singh VP. 2000. Integrated use of organic and fertilizer nitrogen in rice (Oryza sativa) under partially reclaimed sodic soil. Indian J. Agric. Sci. 70(2):114-116. Reddy PM, Hernandez-Oane RJ, Kouchi H, Stacey G, Ladha JK. 2000. Exploring the genetic potential of rice for forming symbiotic associations with rhizobia. In: Pedrosa FO, Hungria M, Yates MG, Newton WE, editors. Nitrogen fixation: from molecules to crop productivity. Dordrecht (The Netherlands): Kluwer Academic Publishers. p 331-332. Reddy PM, Ladha JK. 2000. Nitrogen fixation in rice: Objectives and achievements. In: Pedrosa FO, Hungria M, Yates MG, Newton WE, editors. Nitrogen fixation: from molecules to crop productivity. Dordrecht (The Netherlands): Kluwer Academic Publishers. p 641-646. Roebeling PC, Jansen HGP, Schipper RA, Sáenz F, Castro E, Ruben R, Hengsdijk H, Bouman BAM. 2000. Farm modeling for policy analysis on the farm and regional level. In: Bouman BAM, Jansen HGP, Schipper RA, Hengsdijk H, Nieuwenhuyse A, editors. Tools for land use analysis on different scales; with case studies for Costa Rica. Dordrecht (The Netherlands): Kluwer Academic Publishers. p 171-198. Roetter RP, Hoanh CT, Aggarwal PK, Ismail AB, Lai NX, Lansigan FP, Laborte FP, Van Ittersum MK, De Ridder N, Van Diepen CA, Van Keulen H. 2000. Matching systems methodology development with stakeholders’ needs for agricultural land-use planning: the SysNet experience in Asia, 1996-99. CD-ROM Proceedings SAAD-3, CIP, Lima, Peru, 8-10 Nov 1999.

Roetter RP, Hoanh CT, Aggarwal PK, Van Keulen H. 2000. Challenges, project strategy, and major accomplishments. In: Roetter RP, Van Keulen H, van Laar HH, editors. Synthesis of methodology development and case studies. SYSNET Rep. Pap. Ser. 3. p 3-10. Roetter RP, Laborte AG, Van Oort P, Hoanh CT, Cabrera JMCA, Lucas M, Francisco S, Van Keulen H. 2000. Resource-use analysis at regional scale: explorations for rice systems in Southeast Asia. CD-ROM Proceedings SAAD3, CIP, Lima, Peru, 8-10 Nov 1999. Roetter RP, Van de Geijn SC. 1999. Climate change effects on plant growth, crop yield and livestock. Clim. Change 43:651-681. Rohilla R, Singh VP, Singh US, Singh RK, Khush GS. 2000. Crop husbandry and environmental factors affecting aroma and other quality traits. In: R.K. Singh, editor. Aromatic rices. Engfield (USA) and Plymouth (UK): Science Publishing. p 201-216. Saxena SS, Ladha JK, Gyaneshwar P, ReinholdHurek B, Hernandez RJ, Biswas JC. 2000. Evaluation of lacZ and gusA markers to study rhizobial colonization in rice roots. Indian J. Microbiol. 40:15-20. Schipper RA, Bouman BAM, Jansen HGP, Hengsdijk H, Nieuwenhuyse A. 2000. Integrated biophysical and socio-economic analysis of regional land use. In: Bouman BAM, Jansen HGP, Schipper RA, Hengsdijk H, Nieuwenhuyse A, editors. Tools for land use analysis on different scales; with case studies for Costa Rica. Dordrecht (The Netherlands): Kluwer Academic Publishers. p 115-144. Sheehy JE, Mitchell PL, Dionora MJA, Tadashi T, Peng SB, Khush GS. 2000. Unlocking the yield barrier in rice through a nitrogen-led improvement in the radiation conversion factor. Plant Prod. Sci. 3(4):372-374. Shepherd G, Buresh RJ, Gregory PJ. 2000. Land use affects the distribution of soil inorganic nitrogen in smallholder production systems in Kenya. Biol. Fertil. Soils 31:348-355. Shrestha RK, Ladha JK. 2000. Recycling of residual soil nitrogen in a lowland rice-sweet pepper cropping system. Soil Sci. Soc. Am. J. 64:1689-1698.

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Singh AP, Wade LJ, Tripathi RS. 2000. Dynamics of nutrient release and capture in rainfed lowland rice ecosystem in relation to sufficiency or insufficiency of water. In: Book of abstracts. Third International Crop Science Congress, Hamburg. p 52. Singh RK, Singh CV, Sinha PK, Singh VP, Maiti D, Prasad K. 2000. Effect of soil texture and moisture regime on root and shoot development of upland rice (Oryza sativa) cultivars. Indian J. Agric. Sci. 70(11):730-735. Singh VP, Singh RK, editors. 2000. Rainfed rice: Best practices and strategies in eastern India. IRRI, ICAR, IFAD and IIRR. 292 p. Singh VP, Singh RK. 2000. Training resource book for ecosystems analysis and the design of onfarm experiments. ICAR and IRRI. 70 p. Siopongco J, Quintana L, Harnpichitvitaya D, Rajatasereekul S, Sarawgi AK, Kumar A, Ahmed HU, Sarwoto, Singh AK, Sarkarung S, McLaren CG, Rodriguez R, Wade LJ. 2000. Genotype by environment interactions in rainfed lowland rice and implications for rice improvement. Philipp. J. Crop Sci. 25:54. Smithson PC, Mwangi M, Mwaura H, Wandabwa A, Buresh RJ. 2000. Resin-extractable P compared with other “sink”-type and chemical extractants. ASA-CSSA-SSSA 2000 Annual Meeting Abstracts, 5-9 November 2000, Minneapolis, MN. Madison (WI): ASA-CSSASSSA. p 364. Srivastava PC, Dobermann A, Ghosh D. 2000. Assessment of zinc availability to lowland rice in Mollisols of north India. Commun. Soil Sci. Plant Anal. 31:2457-2471. Thönnissen C, Midmore DJ, Ladha JK, Holmer RJ, Schmidhalter U. 2000. Tomato crop response to short-duration legume green manures in tropical vegetable systems. Agron. J. 92:245253. Thönnissen C, Midmore DJ, Ladha JK, Olk DC, Schmidhalter U. 2000. Legume decomposition and nitrogen release when applied as green manures to tropical vegetable production systems. Agron. J. 92:253-260. Trebuil G, Thong-Ngam C, Turkelboom F, Grellet G, Kam SP. 2000. Trends of land use change and interpretation of impacts in the Mae Chan area of northern Thailand. In: Thomas D, Cuc LT, editors. Proceedings on CD-ROM of the

International Symposium II on Montane Mainland Southeast Asia : Governance in the Natural and Cultural Landscape, 1-5 Jul 2000, Chiang Mai, Thailand. 12 p. Tuong TP, Pablico PP, Yamauchi M, Confesor R, Moody K. 2000. Increasing water productivity and weed suppression of wet seeded rice: effect of water management and rice genotypes. J. Exp. Agric. 36:1-19. Tuong TP, Singh AK, Siopongco J, Wade LJ. 2000. Constraints to high yield of dry-seeded rice in the rainy season in a humic tropic environment. Plant Prod. Sci. 3(2):164-172. Van Keulen H, Roetter RP, Hoanh CT. 2000. Scientific challenges. In: Roetter RP, van Keulen H, van Laar HH, editors. Synthesis of methodology development and case studies. SysNet Res. Pap. Ser. 3. p 77-79. Verma SC, Ladha JK, Tripathi AK. 2000. Diversity of endophytic diazotrophs and mechanism of endophytic colonization in deep water rice. In: Pedrosa FO, Hungria M, Yates MG, Newton WE, editors. Nitrogen fixation: from molecules to crop productivity. Dordrecht (The Netherlands): Kluwer Academic Publishers. p 419-420. Wade LJ, Kamoshita A, Yamauchi A, AzhiriSigari, T. 2000. Genotypic variation in response of rainfed lowland rice to drought and rewatering. 1. Growth and water use. Plant Prod. Sci. 3:173-179. Watson AK, Eusebio AA. 2000. The biological weed control program in rice-based cropping systems, a report on the workshop held at the International Rice Research Institute in May 2000. International Bioherbicide Workshop, 56 Jun 2000, Foz do Iguaçu, Brazil. p 16. Watson AK, Gressel J, Sharon A, Dinoor A. 2000. Colletotrichum strains for weed control. In: Prusky D, Freeman S, Dickman M, editors. Colletotrichum. St. Paul (Minnesota): APS Press. p 250-271. White PF, Dobermann A, Oberthür T, Ros C. 2000. The rice soils of Cambodia. I. Soil classification for agronomists using the Cambodian Agronomic Soil Classification System. Soil Use Manage. 16:12-19. Witt C, Biker U, Galicia CC, Ottow JCG. 2000. Dynamics of soil microbial biomass and nitrogen availability in a flooded rice soil

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amended with different C and N sources. Biol. Fertil. Soils 30:520-527. Witt C, Cassman KG, Olk DC, Biker U, Liboon SP, Samson MI, Ottow JCG. 2000. Crop rotation and residue management effects on carbon sequestration, nitrogen cycling, and productivity of irrigated rice systems. Plant Soil 225:263-278. Witt C, Gaunt JL, Galicia CC, Ottow JCG, Neue HU. 2000. A rapid chloroform-fumigation extraction method for measuring soil microbial biomass C and N in flooded rice soils. Biol. Fertil. Soils 30:510-519. Yadvinder-Singh, Dobermann A, Bijay-Singh, Bronson KF, Khind CS. 2000. Optimal phosphorus management strategies for wheatrice cropping on a loamy sand. Soil Sci. Soc. Am. J. 64:1413-1422. Yang J, Peng S, Visperas RM, Sanico AL, Zhu Q, Gu S. 2000. Grain filling pattern and cytokinin content in the grains and roots of rice plants. Plant Growth Reg. 30(3):261-270. Yasuda M, Okada T, Nozoe T. 2000. Characteristics of nitrogen enrichment by biological nitrogen fixation (BNF) on different management of paddy soils in the Tohoku district of Japan. Jpn. J. Soil Sci. Plant Nutr. 71:849-856. Zhang C, Peng S, Bennett J. 2000. Glutamine synthetase and its isoforms in rice spikelets and rachis during grain development. J. Plant Physiol. 156(2):230-233. Entomology and Plant Pathology Adhikari TB, Shrestha A, Basnyat RC, Mew TW. 1999. Use of partial host resistance in the management of bacterial blight of rice. Plant Dis. 83:896-901. Alinia F, Ghareyazie B, Rubia L, Bennett J, Cohen MB. 2000. Effect of plant age, larval age, and fertilizer treatment on resistance of a cry1Abtransformed aromatic rice to lepidopterous stem borers and foliage feeders. J. Econ. Entomol. 93:484-493. Alinia F, Cohen MB, Gould F. 2000. Heritability of tolerance for the Cry1Ab toxin of Bacillus thuringiensis in Chilo suppressalis (Lepidoptera: Crambidae). J. Econ. Entomol. 93:14-17.

Arboleda M, Azzam O. 2000. Inter- and intrasite genetic diversity of natural field populations of rice tungro bacilliform virus in the Philippines. Arch. Virol. 145:275-289. Azzam O, Arboleda M, Umadhyay KML, de los Reyes JB, Cruz FS, Mackenzie A, McNally KL 2000. Genetic composition and complexity of virus populations at tungro endemic and outbreak rice sites. Arch. Virol. 145(12):26432657. Azzam O, Yambao MLM, Muhsin M, McNally KL, Umadhay KML. 2000. Genetic diversity of rice tungro spherical virus in tungro-endemic provinces of the Philippines and Indonesia. Arch. Virol. 145:1183-1197. Bai JF, Choi SH, Ponciano G, Leung H, Leach JE. 2000. Xanthomonas orzyae pv. orzyae avirulence genes contribute differently and specifically to pathogen aggressiveness. Mol. Plant-Microbe Interact. 13:1322-1329. Barrion AT. 1999. Guild structure, diversity, and abundance of spiders in selected nonrice habitats and irrigated rice fields in San Juan, Batangas, Philippines. Philipp. Entomol. 13(2):129-157. Barrion AT. 2000. A new species of the genus Bavia Simon 1877 (Araneae: Salticidae) from the highlands of Sagada, Mt. Province, Luzon Island, Philippines. Philipp. Entomol. 14(1):53-60. Barrion AT. 1999. Population dynamics of web spinners and hunting spiders in selected nonrice habitats in Candelaria, Quezon, Philippines. Asia Life Sci. 8(2):83-114. Barrion AT. 2000. Vertical stratification and prey spectrum of web-building spiders in irrigated rice fields and selected nonrice habitats in three Southern Tagalog provinces in the Philippines. Asia Life Sci. 9(1):67-101. Barrion AT, Jackson RR. 2000. Prey and life cycle of Dindymus pulcher Stål, a snail-eating pyrrhocorid bug from the Philippines. Philipp. Agric. Sci. 83(3):292-304. Bentur JS, Andow DA, Cohen MB, Romena AM, Gould F. 2000. Frequency of alleles conferring resistance to a Bacillus thuringiensis toxin in a Philippine population of Scirpophaga incertulas (Lepidoptera: Pyralidae). J. Econ. Entomol. 93:1515-1521.

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Bentur JS, Cohen MB, Gould F. 2000. Variation in performance on cry1Ab-transformed and nontransgenic rice varieties among populations of Scirpophaga incertulas (Lepidoptera: Pyralidae) from Luzon Island, Philippines. J. Econ. Entomol. 93:1773-1778. Cohen MB, Romena AM, Gould F. 2000. Dispersal by larvae of the stem borers Scirpophaga incertulas (Lepidoptera: Pyralidae) and Chilo suppressalis (Lepidoptera: Crambidae) in plots of transplanted rice. Environ. Entomol. 29: 958-971. Cox P, Jahn GC, Mak S. 1999. Doing it together means doing it better (sometimes): the case for organizational change in agricultural R&D. Proceedings of the 2nd Asia Pacific Conference on Sustainable Agriculture, 18-20 Oct 1999, Phitsanulok, Thailand. Dirie AM, Cohen MB, Gould F. 2000. Larval dispersal and survival of two stem borer (Lepidoptera: Crambidae) species on cry1Abtransformed and non-transgenic rice. Environ. Entomol. 29:972-978. Fischer KS, Barton J, Khush GS, Leung H, Cantrell R. 2000. Collaborations in rice. Science 290:279-280. Gould F, Cohen MB. 2000. Sustainable use of genetically modified crops in developing countries. In: Agricultural biotechnology and the poor. Washington, D.C.: World Bank. p 139-146. Heong KL. 2000. Pest management strategies for sustainable agricultural development in China. In: Jian Liu and Qi Lu, editors. Integrated resource management in the red soil area of South China. Beijing (People’s Republic of China): China Environmental Science Press. p 139-146. Hossain M, Bennett J, Datta S, Leung H, Khush GS. 2000. Biotechnology research in rice for Asia: priorities, focus, and directions. See Social Sciences. Isogai M. Cabauatan PQ, Masuta C, Uyeda I, Azzam O. 2000. Complete nucleotide sequence of the rice tungro spherical virus genome of the highly virulent strain Vt6. Virus Genes 20:1, 79-85. Jahn GC, Beardsley JW. 2000. Interactions of ants (Hymenoptera: Formicidae) and mealy bugs

(Homoptera: Pseudococcidae). Proc. Hawaiian Entomol. Soc. 34: 1-4. Jahn GC, Khiev B, Pol C, Chhorn N, Pheng S, Preap V. 1999. Developing sustainable pest management for rice in Cambodia. In: Proceedings of the 2nd Asia-Pacific Conference on Sustainable Agriculture, 18-20 Oct 1999, Phitsanulok, Thailand. Jahn GC, Cox P, Mak S, Chhorn N. 1999. Farmer participatory research on rat management in Cambodia. In: Singleton G, Hinds L, Leirs H, Zhibin Z, editors. Ecologically based rodent management. Canberra (Australia): Australian Centre for International Agricultural Research. p 358-371. Jahn GC, Pheng S, Khiev B. 1999. Ecological characterization of pest constraints to rice production in Cambodian rainfed lowland ecosystem: statistical limitations. In: Proceedings of the Workshop on Characterizing and Understanding Rainfed Rice Environments, 5-9 Dec 1999, Bali, Indonesia. Jahn GC, Pol C, Khiev B, Pheng S, Chhorn N. 1999. Farmer’s pest management and rice production practices in Cambodian upland and deepwater rice. Baseline survey report no. 7. Phnom Penh: Cambodia-IRRI-Australia Project. Kraker de J, Rabbinge R, Huis A van, Lenterren JC van, Heong KL. 2000. Impact of N fertilization on the population dynamics and natural control of rice leaffolders (Lepidoptera: Pyralidae). J. Int. Pest Manage. 46:225–235. Mew TW, Swings J. 2000. Xanthomonas. In: Lederberg J, editor. Encyclopedia of microbiology. 2nd ed. Vol. 4. p 921-929. Miranda GJ, Aliyari R, Shirako Y. 2000. Nucleotide sequence of a Dianthovirus RNA1-like RNA found in grassy stunt disease rice plants. Arch. Virol. 145:1-14. Miranda GJ, Azzam O, Shirako Y. 2000. Comparison of nucleotide sequences of rice grassy stunt virus indicates occurrence of natural genetic reassortment. Virology 266:2632. Nath PD, Kenyon l, Bartolome VI, McLaren G, Azzam O. 2000. Simple serological assays for detecting rice tungro viruses. Food Agric. Immunol. 12:139-151.

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Pheng S, Adkins S, Olofsdotter M, Jahn GC. 1999. Allelopathic effects of rice on awnless barnyardgrass. Cambodian J. Agric. 2 (1):4248. Pheng S,Adkins S, Olofsdotter M, Jahn GC. 1999. The search for allelopathic rice in Cambodia. In: Proceedings of the 17th Asian-Pacific Weed Science Society Conference, 22-27 Nov 1999, Bangkok, Thailand. Raymundo AK, Briones AM Jr, Ardales EY, Perez MT, Fernandez LC, Leach JE, Mew TW, Ynalvez MA, McLaren CG, Nelson RJ. 1999. Analysis of DNA polymorphism and virulence in Philippine strains of Xanthomonas oryzae pv. oryzicola. Plant Dis. 83:434-440. Savary S, Castilla NP, Willocquet L. 2000. Analysis of the spatio-temporal structure of rice sheath blight epidemics in a farmer’s field. Plant Pathol. 49:1-5. Savary S, Willocquet L, Elazegui FA, Castilla NP, Teng PS. 2000. Rice pest constraints in tropical Asia: quantification of yield losses due to rice pests in a range of production situations. Plant Dis. 84:357-369. Vera Cruz CM, Bai JF, Oña I, Leung H, Nelson RJ, Mew TW, Leach JE. 2000. Predicting durability of a disease resistance gene based on an assessment of the fitness loss and epidemiological consequences of avirulence gene mutation. Proc. Natl. Acad. Sci. 97(25):13500-13505. Yencho GC, Cohen MB, Byrne PF. 2000. Applications of tagging and mapping insect resistance loci in plants. Annu. Rev. Entomol. 45:391-420. Yin Z, Chen J, Zeng L, Goh M, Leung H, Khush GS, Wang GL. 2000. Characterizing rice lesion mimic mutants and identifying a mutant with broad-spectrum resistance to rice blast and bacterial blight. Mol. Plant-Microbes Interact. 13:869-876. Zhiyi C, Xu Zhigang, Mew TW. 1999. The molecular marker of antagonistic genes of Bacillus species. J. Agric. Biotechnol. 7(3):281-286. Zhiyi C, Xu Zhigang, Mew TW. 1999. Study on the population distribution and biodiversity of antagonistic bacteria against Rhizoctonia solani. Acta Phytopathol. Sin. 29(2):97-103.

Zhu YY, Chen H, Fan JH, Wang YY, Li Y, Chen JB, Fan JX, Hu LP, Leung H, Mew TW, Teng PS, Wang ZH, Mundt CC. 2000. Genetic diversity and disease control in rice. Nature 406:718-722. Genetic Resources Center Gong YP, Borromeo T, Lu BR. 2000. Biosystematics of the Oryza meyeriana complex (Oryza L., Poaceae). Plant Syst. Evol. 224:139-151. Jackson MT, Pham JL, Newbury HJ, Ford-Lloyd BV, Virk PS. 1999. A core collection for rice— needs, opportunities, and constraints. In: Johnson RC, Hodgkin T, editors. Core collections for today and tomorrow. Rome (Italy): International Plant Genetic Resources Institute. p 18-27. Lu BR, Naredo MEB, Juliano AB, Jackson MT. 2000. Preliminary studies on the taxonomy and biosystematics of the AA genome Oryza species (Poaceae). In: Jacobs SWL, Everett J, editors. Grasses: systematics and evolution. Melbourne (Australia): Commonwealth Scientific and Industrial Research Organisation. p 51-58. Pham JL, Toll J, Morin SR. 2000. Approach to in situ conservation by the International Rice Genebank. In: Almekinders C, de Boef W, editors. Encouraging diversity: the conservation and development of plant genetic resources. London (UK): Intermediate Technology Publications. p 112-117. Pham JL, Van Hintum Th JL. 2000. Genetic diversity in agro-ecosystems. In: Almekinders C, de Boef W, editors. Encouraging diversity: the conservation and development of plant genetic resources. London (UK): Intermediate Technology Publications. p 8-14. Virk PS, Newbury HJ, Jackson MT, Ford-Lloyd BV. 2000. See Plant Breeding, Genetics, and Biochemistry. Virk PS, Zhu J, Newbury HJ, Bryan GJ, Jackson MT, Ford-Lloyd BV. 2000. See Plant Breeding, Genetics, and Biochemistry.

Publications and seminars

147

Plant Breeding, Genetics, and Biochemistry Alinia F, Ghareyazie B, Rubia L, Bennett J, Cohen MB. 2000. See Entomology and Plant Pathology. Angeles ER, Khush GS. 2000. Genetics of resistance to green leafhopper in five cultivars of rice, Oryza sativa L. SABRAO J. 32:1-4. Azzam O, Arboleda M, Umadhay KML, de los Reyes JB, Cruz FS, Mackenzie A, McNally KL. 2000. See Entomology and Plant Pathology. Azzam O, Yambao MLM, Muhsin M, McNally KL, Umadhay KML. 2000. See Entomology and Plant Pathology. Datta K, Koukolíková-Nicola Z, Baisakh N, Oliva N, SK Datta. 2000. Agrobacterium-mediated engineering for sheath blight resistance of indica rice cultivars from different ecosystems. Theor. Appl. Genet. 100:832-839. Datta SK. 2000. Transgenic rice: development and products for environmentally friendly sustainable agriculture. In: Watanabe K, Komamine A, editors. Challenge of plant and agricultural sciences to the crisis of biosphere on the earth in the 21st century. Texas (USA): Landes Bioscience. p 237-246. Dela Cruz N, Khush GS. 2000. Rice grain quality evaluation procedures. In: Singh RK, Singh US, Khush GS, editors. Aromatic rices. Enfield (USA) and Plymouth (UK): Science Publishers, Inc. p 15-28. Dey M, Datta SK, Torrizo LB, Reddy PM, Ladha JK, Day B, Stacey G. 1999. See Crop, Soil, and Water Sciences. Dey M, Torrizo LB, Chaudhury RK, Reddy PM, Ladha JK, Datta, Datta SK. 1999. See Crop, Soil, and Water Sciences. Fukuta Y, Sasahara H, Tamura K, Fukuyama T. 2000. RFLP linkage map included the information of segregation distortion in a wide cross population between indica and japonica (Oryza sativa L.). Breed. Sci. 50 :65-72. Fukuta Y, Sato T, Morita S, Nagamine T, Tamura K, Yano H, Yagi T. 2000. QTL analysis for rolled leaf induced by dry stress in a rice hybrid population, Milyang 23/Akihikari recombinant inbred lines [in Japanese]. Hokuriku Crop Sci. 35:47-49.

Fischer KS, Barton J, Khush GS, Leung H, Cantrell RP. 2000. See Entomology and Plant Pathology. Gregorio GB, Senadhira D, Htut T, Graham RD. 2000. Breeding for trace mineral density in rice. Food Nutr. Bull. (21):4. Hossain M, Bennett J, Datta SK, Leung H, Khush GS. 2000. See Social Sciences. Jalodar NB, Blackhall NW, Hartman TPW, Brar DS, Khush G, Davey MR, Cocking EC, Power JB. 1999. Intergeneric somatic hybrids of rice [Oryza sativa L. (+) Porteresia coarctata (Roxb.) Tateoka]. Theor. Appl. Genet. 99:570577. Jena KK, Khush GS. 2000. Exploitation of alien species in rice improvement—opportunities, achievements, and future challenges. In: Nanda JS, editor. Rice breeding and genetics. Enfield (USA): Science Publishers, Inc. p 271-285. Joshi SP, Gupta VS, Aggarwal RK, Ranjekar PK, Brar DS. 2000. Genetic diversity and phylogenetic relationship as revealed by intersimple sequence repeat polymorphism in the genus Oryza. Theor. Appl. Genet. 100:1311-1320. Katiyar SK, Chandel G, Tan Y, Zhang Y, Huang B, Nugaliyadde L, Fernando K, Bentur JS, Inthavong S, Constantino S, Bennett J. 2000. Biodiversity of Asian rice gall midge (Orseolia oryzae Wood-Mason) from five countries examined by AFLP analysis. Genome 43:322332. Khush GS. 2000. Taxonomy and origin of rice. In: Singh RK, Singh US, Khush GS, editors. Aromatic rices. Enfield (USA) and Plymouth (UK): Science Publishers, Inc. p 5-13. Khush GS, Leung H. 2000. Plant genome research and breeding strategies for sustainable food production in the 21st century. In: Esaki L, editor. New frontiers of science and technology. Proceedings of the International Conference on Science Frontier, Tsukuba, 1719 Nov 1999, Tsukuba Center, Japan. Tokyo (Japan): Universal Academy Press Inc. p 1527. Lafitte HR, Courtois B. 2000. See Crop, Soil, and Water Sciences. Li Z, Shen L, Courtois B, Lafitte HR. 2000. See Crop, Soil, and Water Sciences.

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Lopez MT, Virmani SS. 2000. Development of TGMS lines for developing two-line rice hybrids for the tropics. Euphytica 114:211-215. Mazumdar-Leighton S, Babu CR, Bennett J. 2000. Identification of novel serine proteinase gene transcripts in the midguts of two tropical insect pests, Scirpophaga incertulas (Wk.)and Helicoverpa armigera (Hb.). Insect Biochem. Mol. Biol. 30:57-68. Nakazaki T, Ihara N, Fukuta Y, Ikehashi H. 2000. Abundant polymorphism in the flanking regions of two loci for basic PR-1 proteins as markers for indica-japonica differentiation in rice (Oryza sativa L.). Breed. Sci. 50:173-181. Peng S, Laza R, Visperas R, Sanico A, Cassman KG, Khush GS. 2000. See Crop, Soil, and Water Sciences. Quimio CA, Torrizo LB, Setter TL, Ellis M, Grover A, Abrigo EM, Oliva NP, Ella ES, Carpena AL, Ito O, Peacock WJ, Dennis E, Datta SK. 2000. Enhancement of submergence tolerance in transgenic rice overproducing pyruvate decarboxylase. J. Plant Physiol. 156:516-521. Rohilla R, Singh VP, Singh US, Singh RK, Khush GS. 2000. See Crop, Soil, and Water Sciences. Sanchez AC, Brar GS, Huang N, Li Z, Khush GS. 2000. Sequence-tagged site, marker-assisted selection for three bacterial blight resistance genes in rice. Crop Sci. 40:792-797. Sheehy JE, Mitchell PL, Dionora MJA, Tadashi T, Peng SB, Khush GS. 2000. See Crop, Soil, and Water Sciences. Singh RJ, Khush GS. 2000. Cytogenetics of rice. In: Nanda JS, editor. Rice breeding and genetics. Enfield (USA): Science Publishers Inc. p 287311. Singh RK, Singh US, Khush GS. 2000. Aromatic rices. Enfield (USA) and Plymouth (UK): Science Publishers Inc. 292 p. Sripongpangkul K, Posa GBT, Senadhira D, Brar DS, Huang N, Khush GS, Li Z. 2000. Genes/ QTLs affecting flood tolerance in rice. Theor. Appl. Genet. 101:1074-1081. Tabuchi H, Hashimoto N, Takeuchi A, Terao A. Fukuta Y. 2000. Genetic analysis of semidwarfism oh the japonica rice cultivar Kinuhikari. Breed. Sci. 50:1-7.

Tsunematsu H, Yanoria MJ, Ebron LA, Hayashi N, Endo I, Kato H, Imbe T, Khush GS. 2000. Development of monogenic lines of rice for blast resistance. Breed. Sci. 50:229-234. Tu J, Datta K, Khush GS, Zhang Q, Datta SK. 2000. Field performance of Xa21 transgenic indica rice (Oryza sativa L.), IR72. Theor. Appl. Genet. 101:15-20. Tu J, Zhang G, Datta K, Xu C, He Y, Zhang Q, Khush GS, Datta SK. 2000. Field performance of transgenic elite commercial hybrid rice expressing Bacillus thuringiensis δ-endotoxin. Nat. Biotechnol. 18:1101-1104. Virk PS, Newbury HJ, Jackson MT, Ford-Lloyd BV. 2000. Are mapped or anonymous markers more useful for assessing genetic diversity? Theor. Appl. Genet. 100:607-613. Virk PS, Zhu J, Newbury HJ, Bryn GJ, Jackson MT, Ford-Lloyd BV. 2000. Effectiveness of different classes of molecular markers. Euphytica 112:275-284. Virmani SS, Ahmed MA. 2000. Environmentsensitive genic male sterility (EGMS) in crops. Adv. Agron. 72:139-195. Zhang C, Peng S, Bennett J .2000. See Crop, Soil, and Water Sciences. Zhongchao Y, Chen J, Zeng L, Goh M, Leung H, Khush GS, Wang GL. 2000. See Entomology and Plant Pathology. Social Sciences Abedullah, Pandey S. 2000. Risk and the value of rainfall forecasts to rainfed rice farmers in the Philippines. Philipp. J. Crop Sci. Aggarwal PK, Kalra N, Kumar S, Pathak H, Bandyopadhyay SK, Vasisht AK, Roetter RP, Hoanh CT. 2000. See Crop, Soil, and Water Sciences. Centeno HGS, Dawe DD, Hammer GL, Sheehy JE. 2000. See Crop, Soil, and Water Sciences. Dawe D, Dobermann A, Moya P, Abdulrachman S, Bijay-Singh, Lal P, Li SY, Lin B, Panaullah G, Sariam O, Singh Y, Swarup A, Tan PS, Zhen QX. 2000. How widespread are yield declines in long-term experiments in Asia? Field Crops Res. 66:175-193. Dobermann A, Dawe D, Roetter R, Cassman KG. 2000. See Crop, Soil, and Water Sciences.

Publications and seminars

149

Garcia YT, Garcia AG, Oo M, Hossain M. 2000. Income distribution and poverty in irrigated and rainfed ecosystems: the Myanmar case. Econ. Polit. Weekly 35(52 and 53). Hoanh CT, Lai NX, Hoa VTK. 2000. Can Tho Province case study: land use planning under the economic reform. In: Roetter RP, Van Keulen H, Van Laar HH, editors. Synthesis of methodology development and case studies. SysNet Res. Pap. Ser. 3. p 47-52. Hossain M. 2000. Demand-supply balance for rice in Asia: a long-term outlook. In: Asian media and rice. Bangkok (Thailand): The Asia Rice Foundation. p 9-18. Hossain M, Bennett J, Datta S, Leung H, Khush G. 2000. Biotechnology research in rice for Asia: priorities, focus, and directions. In: Qaim M, Krattiger AF, von Braun J, editors. Agricultural biotechnology in developing countries: towards optimizing the benefits for the poor. Dordrecht (The Netherlands): Kluwer Academic Publishers. p 99-120. Hossain M, Bose M. 2000. Growth and structural changes in Bangladesh agriculture: implications for strategies and policies for sustainable development. In: Sattar MA, editor. The changing rural economy of Bangladesh. Dhaka: Bangladesh Economic Association. p 1-20. Hossain M, Gascon F, Marciano E. Income distribution and poverty in rural Philippines: insights from repeat village study. Econ. Polit. Weekly 35 (52 and 53). Hossain M, Sen B, Rahman ZH. 2000. Growth and distribution of rural income in Bangladesh: analysis based on panel survey data. Econ. Polit. Weekly 35 (52 and 53). Hossain M, Singh VP. 2000. Fertilizer use in Asian agriculture: implications for sustaining food security and the environment. Nutr. Cycl. Agroecosyst. 57:155-169. Isvilanonda S, Ahmad A, Hossain M. 2000. Recent changes in Thailand’s rural economy: evidences from a case study of six villages. Econ. Polit. Weekly 35 (52 and 53). Janaiah A. 2000. Economic impact of crop management on performance of hybrid and inbred varieties of rice (Oryza sativa) in India: evidences from farm level study. Indian J. Agric. Sci. 70(2):77-84.

Janaiah A, Bose ML, Agarwal AG. 2000. Poverty and income distribution in rainfed and irrigated ecosystems: village studies in the Chattisgarh Region. Econ. Polit. Weekly 35 (52 and 53). Janaiah A, Hossain M. 2000. Growth and instability of rice-wheat system in India: comparative analysis in high- vs low-productive regions. India Grains 2(1):21-34. Janaiah A, Hossain M. 2000. Issues for policy intervention to promote hybrid rice technology in India: a few lessons from recent experiences. India Grains 2(9):11-15. Kam SP, Hoanh CT, Alvaran A. 2000. See Crop, Soil, and Water Sciences. Laborte AG, Roetter RP, Nuñez B, Hoanh CT, Dreiser C. 2000. Development of a tool for interactive land use scenario analysis: IMGLP user interface. In: Roetter RP, van Keulen H, van Laar HH, editors. Synthesis of methodology development and case studies. SysNet Res. Pap. Ser. 3. p 57-68. Ladha JK, Dawe D, Ventura TS, Singh U, Ventura W, Watanabe I. 2000. See Crop, Soil, and Water Sciences. Pandey S. 2000. Promoting sustainable development in less-favored areas: technologies for Southeast Asian uplands. In: Pender J, Hazell P, editors. Promoting sustainable developments in less favorable areas. Policy brief. Washington, D.C.: International Food Policy Research Institute, Pandey S, Khiem NT, Waibel H, Hong NH, Velasco L, editors. 2000. Commercialization, land-use changes, and food security in the uplands of northern Vietnam. Proceedings of a workshop held in Vietnam. Pham JT, Toll J, Morin S. 2000. See Genetic Resources Center. Roetter RP, Hoanh CT, Aggarwal PK, van Keulen H. 2000. See Crop, Soil, and Water Sciences. Thakur J, Bose ML, Hossain M, Janaiah A. 2000. Rural income distribution and poverty in Bihar: insights from village studies. Econ. Polit. Weekly 35 (52 and 53). Ut TT, Hossain M, Janaiah A. 2000. Modern farm technology and infrastructure in Vietnam: impact on income distribution and poverty. Econ. Polit. Weekly 35 (52 and 53). van Keulen H, Roetter RP, Hoanh CT. 2000. See Crop, Soil, and Water Sciences.

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Biometrics
Amarante ST, Olea A, Harnpichitvitaya D, Naklang K, Wihardjaka A, Sengar SS, mazid MA, Singh G, McLaren CG, Nieuwenhuis P, Wade LJ. 2000. See Crop, Soil, and Water Sciences. Nath PD, Kenyon I, Bartolome VI, McLaren G, Azzam O. 2000. See Entomology and Plant Pathology. Raymundo AK, Briones AM Jr., Ardales EY, Perez MT, Fernandez LC, Leach JE, Mew TW, Ynalvez MA, McLaren CG, Nelson RJ. 1999. See Entomology and Plant Pathology. Siopongco J, Quintana L, Harnpichitvitaya D, Rajatasereekul S, Sarawgi AK, Kumar A, Ahmed HU, Sarwoto, Singh AK, Sarkarung S, McLaren CG, Rodriguez R, Wade LJ, 2000. See Crop, Soil, and Water Sciences. Outposted staff Bounphanousay C, Appa Rao S, Kanyavong K, Inthapanya P, Schiller JM. 2000. Wild rice in the Lao PDR. In: Proceedings of the International Meeting on Conservation Methodologies and Genetics of Wild Rice, 1920 Dec 2000,Vientiane, Lao PDR. Inthapanya P, Sipaseuth, Sihavong P, Sihathep V, Chanhphengsay M, Fukai S, Basnayak J. 2000. Genotypic performance under fertilized and non-fertilized conditions in rainfed lowland rice. Field Crops Res. 65:1-14. Inthapanya P, Sipaseuth, Sihavong P, Sihathep V, Chanhphengsay M, Fukai S, Basnayak J. 2000. Genotypic differences in nutrient uptake and utilization for grain yield production of rainfed lowland rice under fertilized and non-fertilized conditions. Field Crops Res. 65:57-68. Magor NP. 2000. Keeping the focus on the household. In: People’s livelihoods at the landwater interface: emerging perspectives on interactions between people and the floodplain environment. Clemett A, Chadwick MT, Barr JFF, editors. UK: University of Leeds and University of Newcastle. p 74-79. Sengar SS, Wade LJ, Baghel SS, Singh RK. 2000. Effect of nutrient management on rice (Oryza sativa) in rainfed lowland of Southeast Asia. Indian J. Agron. 45(1):158-164.

Senxua P, Linquist B. 2000. Nutrient management for rainfed lowland rice in the Lao PDR. In: Proceedings of the Workshop on Improving Soil Fertility Management in Southeast Asia, 21-23 Nov 2000, Bogor, Indonesia. Singh RK. 2000. Rice research and development strategies for food security in South Asia. India Grains 4:23-28. Singh RK. 2000. Sustaining food security through global partnership in rice research. Rice India 1:87-88. Singh VP. 2000. Rainfed rice: a source book for the best practices and strategies in eastern India. In: Singh VP, Singh RK, editors. International Rice Research Institute, International Fund for Agricultural Development, Indian Council for Agricultural Research, and International Institute for Rural Reconstruction. 292 p. Sipaseuth, Sihavong P, Sihathep V, Inthapanya P, Chanphengsay M, Fukai S. 2000. Development of direct seeding technology packages for rainfed lowland rice in Laos. In: Proceedings of the International Workshop on Direct Seeding, Bangkok, Thailand. Tang SX. 2000. Rice seedling throwing in China: an overview. In: Proceedings of the Workshop on Direct Seeding in Asian Rice Systems. Tang SX, Ding L. 2000. Research on upland rice in the International Rice Research Institute. World Agric. 5:20-22. Wei XH, Tang SX, Yu HY, Jiang YZ, Qiu ZE. 2000. Studies on methods of developing a core collection for China traditional japonica rice germplasm. Chin. J. Rice Sci. 14(4):237-240.

Rice research seminars
Yield and productivity trends in the intensive ricebased cropping systems of Asia. Dr. D. Dawe. The burden of a treasure: IRRI’s long-term experiments. Dr. A. Dobermann. The virology program at IRRI: what happened in the last five years? Dr. O. Azzam. Ecological characterization of biotic constraints to rice production. Dr. G.C. Jahn. Rural-urban migration, urbanization, and alleviation of poverty: the Bangladesh case. Dr. M. Hossain and Dr. R. Afsar, research fellow, Bangladesh Institute of Development Studies.

Publications and seminars

151

Rice seed health for crop and pest management. Dr. T.W. Mew. Striga, a major cause of food insecurity and poverty, can be beaten. Dr. A. Watson. Ecological effects of gene flow from transgenic crops to weeds. Dr. A. Snow, associate professor, Ohio State University. Predicting durable resistance based on cost of pathogen adaptation. Dr. J.E. Leach. Breaking the spiral of nonsustainability. Dr. S.P. Kam. Study of lowland-upland interactions in mountainous areas of the Red River Basin (Vietnam): implications for innovation diffusion. Dr. J.-C. Castella. Soil organic matter, nitrogen availability, and the yield decline under intensive lowland rice cropping. Dr. D. Olk, consultant. Performance of converted Bt corn hybrids against Asiatic corn borer under limited field release condition in the Philippines. Dr. E.C. Fernandez, university researcher and deputy director, Institute of Plant Breeding, University of the Philippines Los Baños. International collaboration in crop improvement research: the case of wheat and rice. Dr. P.L. Pingali, director, Economics Program, International Maize and Wheat Improvement Center, Mexico. Sugarcane viruses: old and new. Dr. G.R. Smith, senior research scientist, David North Plant Research Centre, Bureau of Sugar Experiment Stations, Australia. Fighting micronutrient deficiency—improving food and nutrition vs supplementation. Prof. M.B. Krawinkel, MD, professor of human nutrition, Nutrition in Developing Countries, University of Giessen, Germany. Aerobic rice breeding and production in China. Prof. Wang Hua Qi, chief, Upland Rice Laboratory, Department of Plant Genetics and Breeding, China Agricultural University, China. New approaches to assessment: the case of IPM research at the IARCs. Dr. H. Waibel, professor, agricultural economics, Hanover University, Germany. Management of research institutions at different stages of development. Dr. F.A. Bernardo, consultant.

Exploiting biodiversity for sustainable pest management: from concepts to practice. Ms. I. Revilla. Can anything be done to prevent yield barriers limiting future rice production? Dr. J. Sheehy.

Division seminars
Crop, Soil, and Water Sciences Increasing the soil microbial biomass in rice-wheat crop rotation system may help to reduce environmental risk. Dr. K. Inubushi, professor of horticulture, Chiba University, Japan. Effects of controlled-release coated urea in microbial biomass in three paddy soils. Mr. S. Acquaye, PhD student, Chiba University, Japan. Alternative rice straw management practices in California: new avenues to enhance its viability. Dr. C. van Kessel, professor and agronomist, University of California-Davis, USA. Interaction of diazotrophic endophytes with rice: factors governing colonization and nitrogen fixation. Dr. G. Prasad. Calmodulin–binding cahnnels in plants: targets for manipulating heavy metal tolerance? Dr. S. Ramanjulu, candidate, plant physiologist. Photosynthesis and possible nonphotosynthetic growth regulation under elevated CO2. Dr. S. Seneweera, candidate, plant physiologist. Tillage and crop establishment research in the ricewheat consortium. Dr. P.R. Hobbs, Rice-Wheat regional representative, Centro Internacional de Mejoramiento de Maiz y Trigo, South Asia Regional Office, Kathmandu, Nepal. Groundwater: an endangered resource from intensive rice-based cropping system Mr. A. Castañeda. Yield gaps in farmer’s fields of two intensive irrigated rice sytems. Mr. G. Simbahan. Tolerance for drought and temperature extremes in cowpea. Dr. A.M. Ismail, candidate, plant physiologist. Techniques for measuring hydraulic conductivity in plants (pressure chambers, root pressure probe). Mr. B. Stumpf, Department of Plant Ecology, University of Bayreuth, Germany.

152

IRRI program report for 2000

Effect of climate, agrohydrology, and management on rainfed rice production in Central Java, Indonesia: a modeling approach. Ms. A. Boling. Methods for nonradioactive detection in microplates: fluorescence, fluorescence polarization, time-resolved fluorescence, luminescence, absorbance, and nephelometry. Dr. J. Balmer, director, BMG Labtechnologies Pty. Ltd., Victoria, Australia. On-farm seed priming to reduce risk and increase yield in rainfed environment. Dr. D. Harris, University of Wales, Bangor, UK. Methods and equipment developed in Silsoe and Rothamsted for manipulation of soil strength, study of root growth in strong soil, and associated changes in the plant, the root, and the root tip. Dr. L. Clark, research scientist, Silsoe Research Institute, Bedford, UK. Development of a leaf color chart (LCC) for rice varieties in California. Dr. R. Mutters, University of California Cooperative Extension, Oroville, California, USA. Analysis of zinc deficiency tolerance in rices in the IRRI problem soil germplasm database. Ms. C. Guerta. Simple and cost-efficient method of determining short- and long-term anaerobic and aerobic microbial activity and the response on specific manipulating agents by digital manometry. Mr. M. Robertz, Tintometer GMBH, Germany. Product demonstration of photosynthesis analyzer. Mr. S. Bonnage, ADB Bioscientific, England. Entomology and Plant Pathology Bacterial wilt of potato caused by Ralstonia solanacearum biovar 2A: ecology and management of the pathogen in Nepal. Dr. P. Pradhanang, candidate, affiliate scientist. Molecular genetic analysis of microbial populations. Dr. D. Pearce, candidate, affiliate scientist. Control of planthoppers and leafhoppers in rice by the spider Atypena formosana. Dr. L. Sigsgaard. Managing weeds with disease. Dr. A. Watson. Burkholderia cepacia—a complex example of polyphasic taxonomy. Dr. P. Vandamme,

Laboratory of Microbiology, University of Gent, Belgium. Characterization of the nucleotide sequence of dianthovirus RNA1-like genome detected in grassy stunt disease of rice plants. Dr. G.J. Miranda. Natural and transgenic resistance to tungro viruses. Dr. F. Sta Cruz. Tungro here, there, and everywhere. Mr. R. Cabunagan. Plant Breeding, Genetics, and Biochemistry Genetics of high iron rice. Tin Htut, PhD scholar. Hybrid rice business of Mitsui Chemicals. Atsushi, Nakamura, Mitsui Chemicals, Inc., Japan. Rice blast resistance: development of NILs and genetic analysis. Dr. H. Tsunematsu, consultant, IRRI-Japan Collaborative Project. Apomixis: an inducible hybrid phenotype for crop improvement. Dr. J.G. Carman, Utah University, Logen, USA. Molecular genetics of seed vigor in Beta vulgaris. Dr. B. delos Reyes, USDA-ARS, East Lansing, Michigan, USA. Genes and promoters for apomictic rice. Dr. A. Kathiresan. Wheat transformation at CIMMYT: introducing PR protein genes for disease resistance. Dr. A. Pellegrineschi, CIMMYT, Mexico. Genetic analysis and development of near-isogenic lines for resistance to bacterial blight in rice cultivars. Dr. Kyu-Seong Lee. Effect of WA cytoplasm on some biotic stresses and grain quality traits in some Basmati rice hybrids. Mr. Faiz Ahmad Faiz, research scholar. Social Sciences Mapping rice: today and tomorrow. Mr. A. Rala. Early experiences of hybrid rice adoption in Bangladesh: socioeconomic assessment. Mr. M. Husain, Bangladesh Rural Advancement Committee, Bangladesh. Impact of agricultural research on economic growth and poverty reduction in both China and India. Dr. S. Fan, International Food Policy Research Institute, Washington, D.C.

Publications and seminars

153

The role of agricultural research in poverty reduction. Dr. K. Otsuka, Tokyo Metropolitan University, Tokyo, Japan. Sustainability of intensive rice-wheat systems in Indian Punjab. Dr. J. Singh, Punjab Agricultural University, India. How has the working woman fared? A village-level case study of rural landless laborers in Indian households, 1977-99. V.K. Ramachandran, Indian Statistical Institute. Using ENSO climate data to enhance food security in Indonesia. Drs. W. Falcon, R. Naylor, and D. Rochberg, Stanford University, USA. Multi-agent simulation: an approach to integrated natural resource management. F. Bosquet.

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IRRI program report for 2000

Staff changes

January Dr. Paul Marcotte, former vice chairman of the International Agricultural Development Program, University of California, Davis, joined as head, Training Center. Dr. Roland J. Buresh, former principal soil scientist, International Centre for Research in Agroforestry, Nairobi, Kenya, joined as soil scientist, Crop, Soil, and Water Sciences Division. Dr. Glenn B. Gregorio, former project scientist, joined as affiliate scientist, Plant Breeding, Genetics, and Biochemistry Division. Dr. Christian Witt, former project scientist, joined as affiliate scientist, Crop, Soil, and Water Sciences Division. Dr. Madduma P. Dhanapala, former director, Rice Research and Development Institute, Sri Lanka, joined as affiliate scientist, Crop, Soil, and Water Sciences Division. Dr. Ren Wang, former vice president, Chinese Academy of Agricultural Sciences, China, joined as deputy director general for research. Dr. Mark A. Bell, appointed as head, International Programs Management Office. Dr. Kenneth Schoenly, insect ecologist, Entomology and Plant Pathology Division, left after completing his assignment. Dr. Ossmat Azzam, virologist, Entomology and Plant Pathology Division, left after completing her assignment. Dr. Syed Nurul Alam, consultant, Entomology and Plant Pathology Division, left after completing his assignment. Dr. Hum Nath Bhandari, consultant, Social Sciences Division, left after completing his assignment.

Dr. Pompe Sta. Cruz joined as consultant, Crop, Soil, and Water Sciences Division. Dr. Chang-In Yang, collaborative research fellow, Genetic Resources Center, left after completing his assignment. Ms. Lita Norman joined as collaborative research fellow, Agricultural Engineering Unit. Dr. Rita Afzar joined as consultant, Social Sciences Division. Dr. Vijay Gadkar joined as consultant, Crop, Soil, and Water Sciences Division. Dr. AbuBakr AbdelAziz Mohamed joined as project scientist, Crop, Soil, and Water Sciences Division. February Dr. Achim Dobermann, soil nutrient specialist, Crop, Soil, and Water Sciences Division, resigned. Dr. Fida M. Abbasi joined as collaborative research fellow, Plant Breeding, Genetics, and Biochemistry Division. Dr. Fred Gould joined as consultant, Entomology and Plant Pathology Division, and left after completing his assignment on the same month. Dr. Yolanda Garcia joined as consultant, International Programs Management Office, and left after completing her assignment on the same month. Dr. S.V. Subbaiah joined as consultant, Crop and Resource Management Network (CREMNET). Mr. Walter Rockwood joined as consultant, Communication and Publications Services. Dr. Sena Balachandran joined as project scientist, Plant Breeding, Genetics, and Biochemistry Division.

Staff changes

155

Dr. Young-Chan Cho joined as collaborative research fellow, Plant Breeding, Genetics, and Biochemistry Division. Mr. Olivier Huguenin-Elie, collaborative research fellow, Crop, Soil, and Water Sciences Division, left after completing his assignment. Dr. S. Elangovan, project scientist, CREMNET, resigned. Dr. You-Chun Song joined as collaborative research fellow, Plant Breeding, Genetics, and Biochemistry Division. March Mr. Ian M. Wallace, appointed as director for administration and human resources. Dr. Casiana M. Vera Cruz, former consultant in Entomology and Plant Pathology Division, appointed as plant pathologist. Dr. Takuhito Nozoe, former senior researcher, Laboratory of Macro-components, National Institute of Agro-environmental Sciences, Japan, joined as agronomist, Crop, Soil, and Water Sciences Division. Dr. Rita Afzar, consultant, Social Sciences Division, left after completing her assignment. Dr. S.V. Subbaiah, consultant, CREMNET, left after completing his assignment. Mr. Robert Hill, consultant, Public Awareness, left after completing his assignment. Dr. Im-Soo Choi joined as visiting scientist, Plant Breeding, Genetics, and Biochemistry Division. Dr. Niranjan Baisakh joined as visiting scientist, Plant Breeding, Genetics, and Biochemistry Division. Ms. Hendrika H. van Laar, consultant, Crop, Soil, and Water Sciences Division, left after completing her assignment. Dr. Satoshi Kubota, project scientist, Crop, Soil, and Water Sciences Division, left after completing his assignment. Dr. V. Manoharan, project scientist, Crop, Soil, and Water Sciences Division, left after completing his assignment. Dr. Shin Mun-sik, collaborative research fellow, Plant Breeding, Genetics, and Biochemistry Division, left after completing his assignment.

Dr. Wenjun Zhang, project scientist, Entomology and Plant Pathology Division, left after completing his assignment. Dr. Dirie Ahmed, project scientist, Entomology and Plant Pathology Division, left after completing his assignment. Dr. Changjian Wu, project scientist, Entomology and Plant Pathology Division, left after completing his assignment. Dr. Hiroshi Tsunematsu, consultant, Plant Breeding, Genetics, and Biochemistry Division, left after completing his assignment. Dr. Jagir S. Sidhu, project scientist, Plant Breeding, Genetics, and Biochemistry Division, left after completing his assignment. Dr. Yu Sibin, project scientist, Plant Breeding, Genetics, and Biochemistry Division, left after completing his assignment. April Dr. Gana P. Ohja, consultant, Social Sciences Division, left after completing his assignment. Mr. Walter Rockwood, consultant, Communication and Publications Services, left after completing his assignment. Dr. V. Manoharan, project scientist, Crop, Soil, and Water Sciences Division, left after completing his assignment. Dr. Im-Soo Choi, visiting scientist, Plant Breeding, Genetics, and Biochemistry Division, left after completing his assignment. Mr. Li Luping joined as collaborative research fellow, Social Sciences Division. Dr. Corazon Menguito joined as consultant, Plant Breeding, Genetics, and Biochemistry Division. Dr. Ranjit Singh joined as consultant, Plant Breeding, Genetics, and Biochemistry Division. Dr. Vitoon Viriyasakuntorn joined as consultant, International Programs Management Office, and left after completing his assignment on the same month. Dr. Bi Xuezhi, project scientist, Plant Breeding, Genetics, and Biochemistry Division, left after completing his assignment. Mr. Bao-Giang Nguyen, consultant, Social Sciences Division, left completing his assignment.

156

IRRI program report for 2000

Dr. Xiaoping Yu, project scientist, Entomology and Plant Pathology Division, left after completing his assignment. Dr. Wazhong Tan, project scientist, Entomology and Plant Pathology Division, left after completing his assignment. Dr. You-Chun Song, collaborative research fellow, Plant Breeding, Genetics, and Biochemistry Division, left after completing his assignment. May Dr. Christopher Edmonds, affiliate scientist, Social Sciences Division, left after completing his assignment. Mr. Li Luping, collaborative research fellow, Social Sciences Division, left after completing his assignment. Dr. Corazon Menguito, consultant, Plant Breeding, Genetics, and Biochemistry Division, left after completing her assignment. Dr. Changjian Wu, project scientist, Entomology and Plant Pathology Division, left after completing his assignment. Dr. Ranjit Singh, consultant, Plant Breeding, Genetics, and Biochemistry Division, left after completing his assignment. Dr. Chang-Xiang Mao joined as project scientist, Plant Breeding, Genetics, and Biochemistry Division. Ms. Kate Kirk joined as consultant, Office of the Director for Administration and Human Resources, and left after completing her assignment. Dr. C.H.M. Vijayakumar joined as project scientist, Plant Breeding, Genetics, and Biochemistry Division. Mr. Robert Oliver joined as consultant, Crop, Soil, and Water Sciences Division. Dr. Ilyas M. Ahmed, project scientist, Plant Breeding, Genetics, and Biochemistry Division, left after completing his assignment. Mr. Man-Kee Baek, collaborative research fellow, Plant Breeding, Genetics, and Biochemistry Division, left after completing his assignment. Mr. Bo-Kyeong Kim, collaborative research fellow, Plant Breeding, Genetics, and Biochemistry Division, left after completing his assignment.

Mr. Vu Hai Nam, consultant, Crop, Soil, and Water Sciences Division, left after completing his assignment. Dr. Sabariappan Robin, project scientist, Plant Breeding, Genetics, and Biochemistry Division, left after completing his assignment. Mr. Do Minh Phuong, consultant, Crop, Soil, and Water Sciences Division, left after completing his assignment. Ms. Joyce Gorsuch joined as consultant, International Programs Management Office. June Dr. Maria Olofsdotter-Gunnarsen, affiliate scientist, Crop, Soil and Water Sciences Division, left after completing her assignment. Dr. Fida M. Abbasi, collaborative research fellow, Plant Breeding, Genetics, and Biochemistry Division, left after completing his assignment. Dr. Navtej S. Bains, project scientist, Plant Breeding, Genetics, and Biochemistry Division, left after completing his assignment. Mr. Robert Oliver, consultant, Crop, Soil, and Water Sciences Division, left after completing his assignment. Dr. Benjamin Samson, Jr. joined as consultant, Crop, Soil, and Water Sciences Division. Dr. Abubacker J. Ali joined as project scientist, Plant Breeding, Genetics, and Biochemistry Division. Dr. No-Bong Park joined as visiting scientist, Plant Breeding, Genetics, and Biochemistry Division. Mr. Hanwei Mei joined as collaborative research fellow, Plant Breeding, Genetics, and Biochemistry Division. Dr. Alma C. Sanchez, project scientist, Plant Breeding, Genetics, and Biochemistry Division, left after completing her assignment. Dr. Niranjan Baisakh, visiting scientist, Plant Breeding, Genetics, and Biochemistry Division, resigned. Dr. Himanshu Pathak, consultant, Crop, Soil, and Water Sciences Division, left after completing his assignment.

Staff changes

157

Dr. Shailaya Hittalmani, visiting scientist, Plant Breeding, Genetics, and Biochemistry Division, left after completing her assignment. Ms. Genoveva Loresto, project scientist, Genetic Resources Center, left after completing her assignment. July Dr. Zhao Ming, former professor, College of Plant Sciences, China Agricultural University, joined as affiliate scientist, Crop, Soil, and Water Sciences Division. Dr. Gary C. Jahn, crop protection specialist, Cambodia-IRRI-Australia Project, transferred to Entomology and Plant Pathology Division as entomologist. Dr. Jean Louis Pham, IRS seconded from IRD, Genetic Resources Center, left after completing his assignment. Dr. Kenneth S. Fischer, senior adviser, Director General’s Office, left after completing his assignment. Dr. Arnulfo G. Garcia, agronomist and IRRI representative in Myanmar, left after completing his assignment. Ms. Lita Norman, collaborative research fellow, Agricultural Engineering Division, left after completing her assignment. Dr. Alma C. Sanchez rejoined as consultant, Plant Breeding, Genetics, and Biochemistry Division. Dr. Niranjan Baisakh rejoined as project scientist, Plant Breeding, Genetics, and Biochemistry Division. Dr. Xie Guanlin joined as consultant, Entomology and Plant Pathology Division. Dr. Li Xiaofang joined as visiting scientist, Plant Breeding, Genetics, and Biochemistry Division. Dr. M.A. Taher Mia joined as consultant, Entomology and Plant Pathology Division. Dr. M.V.R Murty, consultant, Crop, Soil, and Water Sciences Division, left after completing his assignment. Dr. Madasami Parani, visiting scientist, Plant Breeding, Genetics, and Biochemistry Division, left after completing his assignment. Mr. Shah Faisal, consultant, Training Center, left after completing his assignment.

Ms. Shrestha Samjhana joined as consultant, International Programs Management Office. August Dr. Gary N. Atlin, former associate professor, Plant Science Department, Nova Scotia Agricultural College, Canada, joined as upland rice breeder, Plant Breeding, Genetics, and Biochemistry Division. Mr. Joseph F. Rickman, agricultural engineer, Cambodia-IRRI-Australia Project, transferred to Agricultural Engineering. Dr. Jonathan R.M. Arah, IRS seconded from ITE, Crop, Soil and Water Sciences Division, left after completing his assignment. Dr. Alma C. Sanchez, consultant, Plant Breeding, Genetics, and Biochemistry Division, left after completing her assignment. Dr. Xie Guanlin, consultant, Entomology and Plant Pathology Division, left after completing his assignment. Dr. M.A. Taher Mia, consultant, Entomology and Plant Pathology Division, left after completing his assignment. Dr. Masako F. Yoshida joined as consultant, Social Sciences Division, and left after completing her assignment on the same month. Dr. Edwin Alcantara joined as consultant, Entomology and Plant Pathology Division. Mr. Nguyen van Ngoc joined as consultant, Crop, Soil and Water Sciences Division. Dr. Jianli Wu joined as consultant, Entomology and Plant Pathology Division. Mr. Dai Xiaofeng joined as consultant, Entomology and Plant Pathology Division, and left after completing his assignment on the same month. Dr. Pradeep K. Sharma joined as consultant, Crop, Soil and Water Sciences Division. Mr. Se-Weong Lee joined as visiting scientist, Entomology and Plant Pathology Division. Dr. Abdul Karim Makarim joined as project scientist, Training Center. Dr. Chantal Loyce, project scientist, Crop, Soil, and Water Sciences Division, left after completing her assignment. Ms. Joyce Gorsuch, consultant, International Programs Management Office, left after completing her assignment.

158

IRRI program report for 2000

Dr. Motoyuki Hagiwara, visiting scientist, Crop, Soil, and Water Sciences Division, left after completing his assignment. Mr. Jaap Nieuwenhuis joined as consultant, Crop, Soil and Water Sciences Division. September Dr. Richard Bruskiewich, former postdoctoral research scientist, Human Analysis/ Informatics, Sanger Centre, UK, joined as bioinformatics specialist, Biometrics Unit. Dr. Pradeep K. Sharma, consultant, Crop, Soil, and Water Sciences Division, left after completing his assignment. Dr. Kenneth Fischer joined as consultant, Office of the Deputy Director General for Research. Mr. Jonathan Arah joined as consultant, Crop, Soil, and Water Sciences Division. Ms. Rina Bakker joined as consultant, Training Center. Dr. Lijun Luo joined as visiting scientist, Plant Breeding, Genetics, and Biochemistry Division. Mr. Kuk-Hyun Jung joined as visiting scientist, Plant Breeding, Genetics, and Biochemistry Division, left after completing his assignment on the same month. Dr. Tilathoo Ram joined as project scientist, Plant Breeding, Genetics, and Biochemistry Division. Ms. Hendrika van Laar rejoined as consultant, Crop, Soil and Water Sciences Division. Dr. Md. Golam Ali Fakir joined as consultant, Entomology and Plant Pathology Division. October Dr. Seiji Yanagihara, former senior researcher in International Collaboration Research Section (ICRS), Japan, joined as rice breeder, Crop, Soil, and Water Sciences Division. Dr. Reimund Roetter, Systems Network coordinator, Crop, Soil, and Water Sciences Division, resigned. Dr. Li Xiaofang, visiting scientist, Plant Breeding, Genetics, and Biochemistry Division, left after completing her assignment. Dr. Edwin Alcantara, consultant, Entomology and Plant Pathology Division, left after completing his assignment.

Mr. Nguyen van Ngoc, consultant, Crop, Soil and Water Sciences Division, left after completing his assignment. Mr. Se-Weong Lee, visiting scientist, Entomology and Plant Pathology Division, left after completing his assignment. Dr. Md. Golam Ali Fakir, consultant, Entomology and Plant Pathology Division, left after completing his assignment. Dr. Pham van Du joined as consultant, Crop, Soil, and Water Sciences Division. Dr. Michael Way joined as consultant, Entomology and Plant Pathology Division. Mr. Woon-Ho Yang joined as collaborative research fellow, Crop, Soil, and Water Sciences Division. Dr. Fu Binying joined as project scientist, Plant Breeding, Genetics, and Biochemistry Division. Dr. Monina Escalada joined as consultant, Entomology and Plant Pathology Division. Ms. Joyce Gorsuch joined as consultant, Office of the Director for Administration and Human Resources. Dr. Nguyen Thi Lang joined as visiting scientist, Plant Breeding, Genetics, and Biochemistry Division. Mr. Christopher Meek, consultant, Experiment Station, left after completing his assignment. November Dr. Abdelbagi M. Ismail, former postgraduate plant physiologist, University of California, USA, joined as plant physiologist, Crop, Soil, and Water Sciences Division. Dr. Bao-Rong Lu, germplasm specialist, Genetic Resources Center, left after completing his assignment. Dr. Yu Sibin, project scientist, Plant Breeding, Genetics, and Biochemistry Division, left after completing his assignment. Ms. Hendrika van Laar, consultant, Crop, Soil, and Water Sciences Division, left after completing her assignment. Dr. Pham van Du, consultant, Crop, Soil, and Water Sciences Division, left after completing his assignment. Dr. Michael Way, consultant, Entomology and Plant Pathology Division, left after completing his assignment.

Staff changes

159

Dr. Randall G. Mutters joined as consultant, Crop, Soil, and Water Sciences Division, left after completing his assignment on the same month. Mr. Michael Rutzke joined as consultant, Crop, Soil, and Water Sciences Division, left after completing his assignment on the same month. Mr. Francisco Gabunada joined as consultant, International Programs Management Office. Mr. Mitsuaki Tanabe joined as consultant, Public Awareness, and left after completing his assignment on the same month. Dr. Kyung-Ho Kang joined as collaborative research fellow, Plant Breeding, Genetics, and Biochemistry Division. Dr. Woon-Go Ha joined as collaborative research fellow, Plant Breeding, Genetics, and Biochemistry Division. Dr. Serge Savary joined as consultant, Entomology and Plant Pathology Division. Dr. Seung-Don Lee joined as collaborative research fellow, Entomology and Plant Pathology Division. Mr. Sung-Kee Hong joined as collaborative research fellow, Entomology and Plant Pathology Division. Dr. David Shires joined as consultant, Training Center. Dr. Barney Caton joined as visiting scientist, Crop, Soil, and Water Sciences Division. Dr. Peter Mitchell joined as consultant, Crop, Soil, and Water Sciences Division, left after completing his assignment. December Dr. Martha M. Gaudreau, agroeconomist and team leader, IRRI-Madagascar Rice Research Project, left after completing her assignment. Dr. Pompe Sta. Cruz, consultant, Crop, Soil, and Water Sciences Division, left after completing his assignment. Dr. No-Bong Park, visiting scientist, Plant Breeding, Genetics, and Biochemistry Division, left after completing his assignment. Mr. Hanwei Mei, collaborative research fellow, Plant Breeding, Genetics, and Biochemistry Division, left after completing his assignment.

Dr. Monina Escalada, consultant, Entomology and Plant Pathology Division, left after completing her assignment. Ms. Joyce Gorsuch, consultant, Office of the Director for Administration and Human Resources, left after completing her assignment. Mr. Francisco Gabunada, consultant, International Programs Management Office, left after completing his assignment. Dr. Nguyen Tri Khiem, project scientist, Social Sciences Division, left after completing his assignment. Dr. Serge Savary, consultant, Entomology and Plant Pathology Division, left after completing his assignment. Dr. Geoffrey Norton joined as consultant, Entomology and Plant Pathology Division, left after completing his assignment. Mr. Jiaan Cheng joined as consultant, Entomology and Plant Pathology Division, and left after completing his assignment. Dr. Chris O’Donnell joined as consultant, Social Sciences Division, and left after completing his assignment. Dr. J. Brian Hardaker joined as consultant, Social Sciences Division, and left after completing his assignment. Ms. Shrestha Samjhana, consultant, International Programs Management Office, left after completing her assignment. Mr. Jonathan Arah, consultant, Crop, Soil, and Water Sciences Division, left after completing his assignment. Dr. Gyaneshwar Prasad, project scientist, Crop, Soil, and Water Sciences Division, left after completing his assignment. Ms. Rina Bakker, consultant, Training Center, left after completing her assignment. Mr. Suvit Pushpavesa, consultant, Plant Breeding, Genetics, and Biochemistry Division, left after completing his assignment. Dr. Barney Caton, visiting scientist, Crop, Soil, and Water Sciences Division, left after completing his assignment.

160

IRRI program report for 2000

Finances

IRRI’s audited financial statements, which provide detailed information about the Institute’s finances, are available from the office of the director for

finance. The table below provides information on support from IRRI donors in 2000.

Summary of financial support to the IRRI research agenda, 2000 (US$). Asian Development Bank 1,107,991 Australia 2,267,312 Bangladesh 106,519 Belgium 145,635 Brazil 10,000 Canada Canadian International Development Agency 692,937 International Development Research Centre 200,288 China 130,000 Denmark 1,178,103 European Commission 1,413,877 Francea 438,322 Germany Federal Ministry for Economic Cooperation 377,120 Federal Ministry for Economic Cooperation/ German Agency for Technical Cooperation 741,207 India 158,064 International Fund for Agricultural Development 162,705 Iran 142,692
a

Japan 8,193,930 Korea 314,710 Mexico 15,000 Netherlands 597,277 Norway 116,276 Philippines 212,146 Rockefeller Foundation 1,021,827 Spain 25,000 Sweden 397,797 Switzerland 2,700,500 Thailand 25,000 United Kingdom 2,521,931 United States of America United States Agency for International Development 3,960,285 United States Department of Agriculture 164,672 World Bank 4,068,159 Others 188,160 Total 33,795,442

The Government of France also provided personnel and other services valued at F 2.19 million.

Finances

161

Weather summary

The La Niña phenomenon of 1999 continued until late August of 2000. January until March was a relatively rainy DS with 44 rainy days, which was twice the number of rainy days during normal years. The average amount of rainfall was 6 mm d–1. The lowest recorded pH measurement of rainwater at IRRI for the year was 3.3. Annual rainfall for 2000 was 2,707 mm for the IRRI dryland (upland) site and 2,581 mm for the wetland (lowland) site (Fig. 1). These values were 613 mm higher than the long-term average rainfall for the upland site and 554 mm higher for the lowland site. Los Baños experienced twice as much rainfall in October this year, compared with the long-term amount. The wettest day at IRRI occurred 28 Oct with more than 283 mm rainfall d–1. The longest recorded continuous wet spell was 20 d at the upland site (26 Jun–15 Jul) and 17 d at the low-

land site (28 Jun–14 Jul). The longest continuous dry spell was 12 d at the upland site and in the lowland on three occasions (8–18 Jan, 18–29 Feb, and 25 Apr–6 May). Mean monthly solar radiation reached a peak in April (more than 23 MJ m–2 d–1) and gradually declined to 13 MJ m–2 d–1 in December (Fig. 2). Solar radiation was relatively low during the first decade of July. The highest recorded cumulated solar radiation (30.9 MJ m–2 d–1) occurred 1 May. The average duration of bright sunshine was about 9 h d–1 in April and declined to low values of 4 h d–1 in July. The longest record of sunshine at Los Baños was on 2 May with 11.6 h of bright sunshine. Maximum temperature reached its highest monthly mean value in April (33.9 °C at the upland site and 32.7 °C at the lowland site) then gradually dropped to a lower monthly mean value in Decem-

700 600 500 400

Amount (mm/month)

30 25 20 15

Solar Radiation (MJ/m_/day)

300 200 100 0 J F M A M J J A S O N D

10 5 0 J F M A M J

2000 90% 10%

J

A

S

O

N

D

1. Rainfall and potential evapotranspiration pattern at Los Baños. IRRI, 2000.

2. Mean monthly solar radiation with 10 and 90% probability of occurence. IRRI, 2000.

162

IRRI program report for 1999

40 Temperature (°C) 35 30 25 20 15 10 5 0 J F M A M J J A S O N D 2000 1979-99

4

Maximum
3

Minimum

2

1

Dryland Wetland

0 J F M A M J J A S O N D

3. Maximum and minimum air temperature at the dryland site. IRRI, 1979-2000.

4. Midday vapor pressure deficit at the dryland and wetland sites. IRRI, 2000.

ber (about 29 °C at both sites) (Fig. 3). The recorded averages of maximum temperature were lower than the long-term average in July. The hottest day in Los Baños was on 23 Apr with 36.7 °C of recorded maximum temperature at the upland site. The distribution of minimum temperatures was more stable than the distribution of the maximum temperatures. Minimum air temperatures were generally higher than the long-term monthly averages during the early part of the year. The coldest day for 2000 was 30 Jan with 19.2 °C recorded at the lowland site. Mean early morning relative humidity ranged from 79 to 88%. Midday vapor pressure deficit was consistent with the long-term trend at the lowland site and stayed minimal at the upland site.

Daily mean windspeed, measured at 2-m height was 1.6 m s–1 for the upland site and the lowland site. Windspeed was generally low (<2.0 m s–1) except during the passage of tropical disturbances. Maximum 24-h average windspeed was 7.8 m s–1 at the upland site on 28 Oct. Because of a slightly higher air temperature, lower amount of rainfall, and higher vapor pressure deficit at midday, free water evaporation at the upland site was slightly higher than at the lowland site (Fig. 4). Open-pan evaporation totals were 1,577 mm at the upland site and 1,524 mm at the lowland site. These values were 327 mm lower than the long-term evaporation total at the upland site and 174 mm lower than the long-term evaporation at the lowland site.

Weather summary

163

164

Table 1. Monthly weather data for IRRI and cooperating weather stations in the Philippines, 2000.

Site Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Annual total or daily average

IRRI program report for 1999

Rainfall (mm mo–1)
N, N, N, N, N, N, N, N, 121°15' 121°15' 120°32' 124°47' 124°53' 120°56' 121°22' 122°35' E) E) E) E) E) E) E) E) 68 74 0 68 118 0 350 13 78 68 7 227 393 68 338 63 108 124 19 155 318 86 372 146 64 56 0 93 244 18 122 23 156 125 344 48 345 319 190 171 210 410 227 355 179 1135 113 291 483 367 150 370 286 479 235 354 193 154 527 99 240 186 206 304 227 216 386 33 194 207 341 244 583 611 397 164 308 227 469 475 322 295 16 373 505 128 512 154 291 277 9 248 143 44 761 390 2710 2582 3019 1912 3658 1803 4426 2572

IRRI, dryland site IRRI, wetland site MMSU, Batac, Ilocos Norte Matalom, Leyte MOSCAT, Claveria, Mis. Oriental PhilRice, Muñoz, Nueva Ecija Siniloan, Laguna WESVIARC, Iloilo

(14°13' (14°11' (18°03' (10°17' (08°37' (15°45' (14°10' (10°46'

Solar radiation (MJ m–2 d–1)
14.3 14.2 15.7 20.9 13.5 19.7 17.8 18.7 14.6 14.3 15.8 18.4 13.5 19.4 19.5 17.0 18.2 23.7 18.8 18.5 18.0 23.5 18.5 18.2 18.8 21.0 18.4 18.5 19.3 21.0 21.2 21.1 16.4 18.5 17.7 m 21.4 23.1 19.2 21.2 19.8 23.7 20.4 21.1 19.1 22.2 19.6 17.9 Relative humidity (%) 14.2 13.9 15.7 20.2 m 15.2 17.1 16.2 17.7 17.5 19.0 21.0 m 18.2 18.7 16.5 17.3 17.1 16.6 22.0 m 18.0 17.8 18.2 14.5 14.0 14.6 19.5 m 17.6 18.5 15.8 14.0 13.6 14.8 18.0 m 16.7 17.6 17.2 13.3 13.2 12.6 18.0 m 15.5 16.6 14.5 16.6 16.3 16.8 20.1 15.9 18.8 19.1 17.7

IRRI, dryland site IRRI, wetland site MMSU, Batac, Ilocos Norte Matalom, Leyte MOSCAT, Claveria, Mis. Oriental PhilRice, Muñoz, Nueva Ecija Siniloan, Laguna WESVIARC, Iloilo

IRRI, dryland site IRRI, wetland site MMSU, Batac, Ilocos Norte Matalom, Leyte MOSCAT, Claveria, Mis. Oriental PhilRice, Muñoz, Nueva Ecija Siniloan, Laguna WESVIARC, Iloilo 86 84 84 71 96 83 93 88 87 85 85 73 95 85 94 91 82 79 77 70 94 88 89 86 84 81 81 68 95 87 89 88

84 84 81 72 96 87 92 90

84 81 81 71 95 88 90 89

89 85 87 69 95 91 94 89

85 84 85 69 96 91 91 89

84 82 86 67 95 93 93 86

88 87 86 70 96 90 93 91

88 87 85 74 96 86 m 91

88 88 84 74 96 83 m 92

86 84 84 71 95 88 92 89

Table 1 continued.

Site Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Annual total or daily average

Temperature (°C)

IRRI, dryland site

IRRI, wetland site

MMSU, Batac, Ilocos Norte

Matalom, Leyte

PhilRice, Muñoz, Nueva Ecija

MOSCAT, Claveria, Mis. Oriental

Siniloan, Laguna

WESVIARC, Iloilo

Max Min Max Min Max Min Max Min Max Min Max Min Max Min Max Min 29.5 22.5 28.6 22.3 32.2 18.7 m 21.5 28.3 18.9 30.3 22.2 25.1 20.9 30.4 20.3 29.5 22.9 28.5 22.9 33.5 20.1 m 22.0 28.3 18.8 29.6 22.4 25.4 20.9 30.8 20.9 31.1 23.7 29.9 23.7 34.1 20.7 m 21.7 28.6 19.0 31.1 22.6 26.6 21.9 31.2 21.1 33.8 24.2 32.8 24.2 34.9 22.8 m 22.0 29.4 19.0 33.6 23.9 29.1 22.9 33.3 21.3 33.0 24.1 32.4 24.5 33.0 22.6 m 21.6 30.0 19.9 32.6 24.3 29.2 22.7 32.7 21.3 33.0 24.1 32.1 24.7 33.6 23.5 32.4 22.3 29.2 19.1 33.0 24.4 29.6 22.7 31.7 21.2 30.7 23.5 30.1 24.0 32.2 24.7 32.3 22.4 2.7 19.5 29.8 24.2 27.7 21.6 30.3 20.9 32.1 23.4 31.3 24.0 32.2 23.5 32.3 22.2 29.5 19.2 31.1 24.9 29.3 22.5 30.7 20.2 31.5 24.0 31.0 24.2 31.6 22.7 32.9 23.1 30.5 19.2 30.8 23.9 27.7 21.8 30.9 21.2 31.0 23.9 30.3 24.0 32.5 22.8 32.5 22.0 29.2 19.5 31.6 23.7 28.3 20.2 30.8 20.7 30.6 24.0 29.7 24.0 33.2 21.3 32.0 21.8 29.0 19.5 31.6 23.5 m m 30.9 21.2 29.7 23.8 29.1 24.0 32.8 20.6 32.0 22.3 28.5 18.9 30.5 23.3 m m 29.9 20.4

31.3 23.7 30.5 23.9 33.0 22.0 32.3 22.1 29.2 19.2 31.3 23.6 27.8 21.8 31.1 20.9

Windspeed (m s–1)
1.8 1.9 1.2 1.0 0.8 2.7 4.8 1.1 1.7 1.6 1.3 0.6 0.7 2.4 4.8 0.7 1.5 1.4 1.1 0.8 0.8 1.3 4.1 0.7 1.4 1.3 1.0 0.8 0.8 0.6 2.9 0.5 1.4 1.2 0.9 0.9 0.8 0.5 1.7 0.4 1.1 1.1 0.7 0.6 0.7 0.6 1.6 0.3 1.8 1.8 1.5 1.0 0.7 1.1 1.7 0.5 1.4 1.2 1.1 1.0 0.8 0.5 1.3 0.4 1.9 1.6 0.8 1.0 0.7 0.6 2.4 0.6 1.5 1.4 0.5 0.5 m 1.1 2.0 0.3 1.8 1.7 0.6 0.6 0.5 2.0 4.3 1.1 1.7 1.8 1.3 0.6 0.6 2.9 4.6 0.7 1.6 1.5 1.0 0.8 0.7 1.4 3.0 0.6

IRRI, dryland site IRRI, wetland site MMSU, Batac, Ilocos Norte Matalom, Leyte MOSCAT, Claveria, Mis. Oriental PhilRice, Muñoz, Nueva Ecija Siniloan, Laguna WESVIARC, Iloilo

Evaporation (mm mo–1)
121 116 125 164 112 142 150 116 108 140 145 89 151 136 148 137 161 166 135 171 164 190 187 185 175 146 197 194 148 143 154 184 151 172 173 149 147 156 172 134 172 135 122 120 152 175 146 139 136 142 133 160 180 138 161 120 141 139 134 183 155 71 131 110 103 121 162 136 125 111 99 98 108 143 120 125 113 92 94 117 145 119 107 97 1578 1525 1713 1994 1581 1733 1660

Weather summary

IRRI, dryland site IRRI, wetland site MMSU, Batac, Ilocos Norte MOSCAT, Claveria, Mis. Oriental PhilRice, Muñoz, Nueva Ecija Siniloan Laguna WESVIARC, Iloilo

165

a

WESVIARC = Western Visayas Integrated Agricultural Research Center, MMSU = Mariano Marcos State University, MOSCAT = Misamis Oriental State College of Agriculture and Technology . bm = missing data.