Authenticity of Meat Product_tools Against Fraud

Food Research International 60 (2014) 19–29

Contents lists available at ScienceDirect

Food Research International
journal homepage: www.elsevier.com/locate/foodres

Review

Authenticity of meat products: Tools against fraud
Miguel Ángel Sentandreu ⁎, Enrique Sentandreu
Instituto de Agroquímica y Tecnología de Alimentos (CSIC), Calle Agustín Escardino 7, 46980 Paterna, Valencia, Spain

a r t i c l e

i n f o

Article history:
Received 17 January 2014
Received in revised form 13 March 2014
Accepted 27 March 2014
Available online 4 April 2014
Keywords:
Meat authenticity
Meat fraud
Analytical methods
Consumer's choice

a b s t r a c t
More than ever, people today demand clear and reliable information about the food they consume. This has a
great impact on the economy since the consumer's choice is greatly influenced by the food composition detailed
in labelling. In the case of processed meat products this is going to be especially important because a simple visual
inspection would not allow us to discriminate between the different components so easily as in the case of fresh
meat. In order to assure fair trade, food safety and freedom of choice, honest and accurate food label is a requisite
that must be assured by legal authorities. To do that, robust and reliable methodologies of analysis must be
implemented in control laboratories. In relation to this, the present review intends to give an overview of the
different analytical strategies that have been traditionally used by control laboratories to assess meat authenticity
or that could be interesting alternatives for fraud detection in near future.
© 2014 Elsevier Ltd. All rights reserved.

Contents
Introduction: the problem of meat authentication . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Analytical strategies employed to assess meat authenticity . . . . . . . . . . . . . . . . . . . . . . . .
Non-targeted approaches: use of large dataset and chemometrics . . . . . . . . . . . . . . . . . .
Measurement of stable isotope ratios and trace elements to reveal meat origin and feeding regime
Magnetic resonance to detect the fraudulent addition of water . . . . . . . . . . . . . . . .
Histology and image analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Metabolomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Targeted approaches: study of specific compounds . . . . . . . . . . . . . . . . . . . . . . . . .
Techniques not based on discrimination at sequence level . . . . . . . . . . . . . . . . . . .
Techniques based on discrimination at sequence level . . . . . . . . . . . . . . . . . . . .
Concluding remarks: the art to be authentic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Introduction: the problem of meat authentication
Meat authenticity and traceability are issues of primary importance
in our modern society as it can be deducted, for example, from recent
events regarding adulteration of meat products with non-declared
species such as horse meat (Premanandh, 2013). This illustrates the

⁎ Corresponding author. Tel.: +34 963900022x2103.
E-mail address: [email protected] (M.Á. Sentandreu).

http://dx.doi.org/10.1016/j.foodres.2014.03.030
0963-9969/© 2014 Elsevier Ltd. All rights reserved.

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global claim of consumers worldwide to dispose of clear and reliable
information about the food they consume. This is especially true in the
case of processed meat products where a simple visual inspection
would not allow discriminating between the different components so
easily as in the case of intact fresh meat (Flores-Munguia, BermudezAlmada, & Vazquez-Moreno, 2000). This claim has, of course, important
underlying reasons. Nowadays price and lifestyle, together with different religion or health concerns, can affect the individual's choice on
food products depending on their composition. A good example of this
is the increasing interest of the Muslim community to certificate the

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M.Á. Sentandreu, E. Sentandreu / Food Research International 60 (2014) 19–29

Halal status of the meat they consume in an expanding global meat
market. In relation to this, several reviews have recently been published
addressing this issue (Ali et al., 2012; Farouk, 2013; Nakyinsige, Man, &
Sazili, 2012). Another example is the increasing demand for traditional
and/or regional meat products, which are perceived by consumers as
high quality foods with added-value (Montowska & Pospiech, 2012).
Under this context, honest and accurate food labelling is essential to
assure consumers food safety and choice. In meat products, there is a
requirement to indicate the amount of each ingredient contained in
them, what is known as the Quantitative Ingredient Declaration
(QUID). The declaration establishes a new definition of meat with the
purpose of right product labelling. The definition restricts the term
“meat” to skeletal muscle together with maximum limits for the
connective tissue and fat content. Excess of fat and/or connective tissue
cannot be considered as meat and thus it must be declared separately in
the label. This also implies to indicate and quantify each animal species
contained in the product separately. In addition to this, mechanically
recovered meat (MRM) and other parts of carcass such as the liver,
lung, heart, or tongue, for example, cannot be considered as meat and
need also to be separately identified (Zukal & Kormendy, 2007).
Legal authorities must control that these requirements are effectively carried out by food producers or traders by means of robust and reliable methodologies in order to assure that fraudulent or accidental
mislabelling does not arise, which is normally done with the aim to
obtain additional economic gain (Spink & Moyer, 2011). We must
be aware that these illegal practices seriously damage the image of
both meat as high quality food and the industry associated with the
term “meat”.
The main areas susceptible to fraud in the meat industry would be the
following: 1) the origin of meats and the animal feeding regime (as in the
case of certificated regional products, for example); 2) substitutions
of meat ingredients by other animal species, tissues, fat or proteins;
3) modifications of the processing methods of meat products and
4) additions of non-meat components such as water or additives
(Ballin, 2010).
This review, more than to present a detailed description of the different types of fraud that can occur in the meat industry, will try to give an
overview on the different analytical methods that have been traditionally used by control laboratories to assess meat authenticity. Also, we
will try to explore the potential of new promising approaches as a
way to overcome the existing limitations that are still present in the detection of frauds in certain types of products. We will see that, in some
cases, the same analytical technique can be used to detect different
types of frauds, whereas in other cases different strategies can be used
to detect the same type of fraud.

Analytical strategies employed to assess meat authenticity
Non-targeted approaches: use of large dataset and chemometrics
Generally, data-rich instrumental methods require their coupling to
a multivariate data analysis tool to avoid misleading conclusions that
can put on risk not only the quality of trading products but also, the
consumers' health and habits or the image of a considered brand.
Regarding food fraud, chemometrics is a powerful data reduction solution used qualitatively for grouping or classifying unknown samples
with similar characteristics and quantitatively for determining adulterant analytes in samples (Moore, Spink, & Lipp, 2012) or for assessing
their quality or authenticity (Consonni & Cagliani, 2010). In the particular case of meat and meat products authentication, chemometrics
has mainly been associated with spectroscopy (near/mid-infrared)
approaches (Alamprese, Casale, Sinelli, Lanteri, & Casiraghi, 2013) but
it is also a routine complement for nuclear magnetic resonance (NMR)
and mass spectrometry-based metabolomics (Cubero-Leon, Peñalver,
& Maquet, 2014).

Measurement of stable isotope ratios and trace elements to reveal meat
origin and feeding regime
This type of analyses has traditionally been used to determine the
geographical origin of meats, as well as to know the feeding system
that has been employed to raise the animals. The basis for discrimination relies in the fact that ratios of elements such as hydrogen (2H/1H),
carbon (13C/12C), oxygen (18O/16O), nitrogen (15N/14N) and sulphur
(34S/32S) can vary depending on the geographical origin of soil and
drinking water, as well as on the different animal feeds used in the
farm (pasture or grain, for example). Since these variations will be
incorporated later on into animal tissues, a precise analysis of these
compounds can provide the desired information about the animal
origin and its feeding regime. This can be especially useful at the time
to authenticate regional and traditional meat and meat products, since
they are perceived by consumers such as higher quality and healthier
products, with enhanced flavour characteristics and thus susceptible
for fraud by lower-quality products. Normally, these regional products
are based on extensive production systems where animals live in close
contact with the natural environment and can thus eat the food
resources available in that region (Montowska & Pospiech, 2012). In a
recent study, the stable isotope ratios of the aforementioned elements
have been used to authenticate the origin of Italian PDO (“Protected
Designation of origin”) hams and to distinguish them from other producing areas such as Spanish hams, as well as to evaluate the effect
exerted by the pig genotype and processing conditions on the final
product characteristics (Perini, Camin, del Pulgar, & Piasentier, 2013).
Analysis of C and N stable isotope composition, in addition to the
analysis of 23 trace elements was carried out by Zhao et al. (2013) on
defatted beef samples taken from a total of 69 animals coming from
four different regions in China. Multivariate analysis of the obtained
results showed that each beef sample had a site-specific geographic
profile of element composition, thus allowing a correct determination
of the origin of meat for the whole set of samples used in the study.
Authors emphasised the importance to collect all cattle samples in the
same period of the year, in order to avoid the effect of seasonal variations in animal tissues due to changes in animal's diets. Unfortunately,
the level of 100% classification rate was not obtained in all cases, being
the average of correct traceability around 60–80%. It is easier to obtain
good results when comparing samples coming from distant geographical regions, whereas in the case of neighbouring areas a correct discrimination will be largely dependent on the performance and sensitivity of
the analytical equipment (Montowska & Pospiech, 2012). This situation
was well illustrated in the work of Liu, Guo, Wei, Shi, and Sun (2013),
where they measured the stable isotope ratios of C, N, and H in 167
beef animals coming from seven sub-regions in China by using isotope
ratio mass spectrometry (IRMS). Interestingly, authors considered the
cattle hair tail to perform the isotope ratio analyses instead of using the
more common muscle or fat tissue, being able to correctly classify
around 70% of the samples assayed. This type of biological material
would be easier and cheaper to obtain, handle and transport from cattle
of the different producing areas to the laboratory where the analyses will
be carried out. Thus, future methods should take this in consideration as
a way to simplify the cost and time of analyses.
In the studies aimed at determining the feeding history of meat
animals, variations in the 13C/12C and 15N/14N isotope ratios are normally analysed for that purpose. Variations in carbon isotope ratio can reveal
information about animal's diet, distinguishing plants with different
photosynthetic pathways such as C3 or C4 plants. This is because C3
plants, such as cereals and most fruits, incorporate less 13C than C4
plants (such as maize and sugar) due to the fact that they use different
biochemical pathways to fix CO2 (Primrose, Woolfe, & Rollinson,
2010). The level of 15N/14N is also strongly related to diet. Despite no
significant differences have been found between C3 and C4 plants,
nitrogen isotope ratio can give information about the different production areas of plant feeds. This is because the particular characteristics
of each region in terms of type of soil, use of chemical fertilisers or

M.Á. Sentandreu, E. Sentandreu / Food Research International 60 (2014) 19–29

manure and the particular air composition of the area will introduce
appreciable changes in 15N/14N isotope ratio values of plants that will
be further incorporated by animals (Vinci, Preti, Tieri, & Vieri, 2013;
Yanagi et al., 2012).
Magnetic resonance to detect the fraudulent addition of water
One of the most common practices of meat adulteration consists in
the addition of water with the objective to increase size, weight and,
consequently, the final price of the product. Even if normally this is
not going to imply any risk for human health, it is going to negatively
affect the final flavour characteristics, resulting in paying an extra cost
for a product of lower quality, reducing the consumer satisfaction. The
traditional approach to reveal this fraud consists of determining the
water/protein ratio by mass difference before and after drying of meat
(Al-Bahouh, 2012; Prayson, McMahon, & Prayson, 2008). An important
limitation of this method is that added water can easily be masked by
the addition of exogenous proteins and phosphate to meat, leaving
the water/protein ratio close to the original value (Ballin, 2010). For
that reason, new and more powerful methodologies based on magnetic
resonance have come up during the last decade aiming to avoid this
limitation. An advantage of these techniques is that they are nondestructive. Nuclear magnetic resonance (NMR) has proved to be useful
in studying the water distribution in fresh meat in relation to quality
parameters such as water holding capacity, tenderness and juiciness
(Bertram & Andersen, 2007; Pearce, Rosenvold, Andersen, & Hopkins,
2011). In the same way, Dolata, Piotrowska, Wajdzik, and Tritt-Goc
(2004) concluded that magnetic resonance imaging (MRI) was adequate for studying the effect of brine injection on water distribution in
cured meats and to optimise the tumbling process in industry. Taken
together, we can conclude that these techniques represent a powerful
approach to detect both the fraudulent addition of water and also the
addition of undeclared substances with the aim to increase the water
retention properties of meat (Bertram & Andersen, 2004). In addition
to this, NMR has shown potential in discriminating fresh from thawed
meat (Ballin & Lametsch, 2008).
Histology and image analysis
Histological techniques based on either light or electron microscopy
combined with digital image analysis have successfully been applied in
the evaluation of the tissue content and detection of morphological
alterations in processed meat products where a simple visual inspection
is not evident. A good example is the work carried out by Prayson et al.
(2008), where they applied electron microscopy to cross-section analysis as a way to estimate the meat content in American hotdogs. They
also estimated the water content in the samples by determining the
water/protein ratio as commented above. The obtained results are
quite interesting since they revealed that in most cases more that 50%
of the total weight of hotdogs was comprised by water. The amount of
meat, represented by skeletal muscle, was in most cases less that 10%
of the cross-sectional area showing also morphological alterations. In
addition to this, other components not properly indicated in the label
such as the bone, plant material or cartilage were also found. The overall
conclusion was that, in view of the low skeletal muscle content found in
the study, the impression that meat was the primary component in
hotdogs seems misleading.
Light microscopy in combination with image analysis has been used
to determine the percentage of skeletal muscle and also to detect the
presence of other animal tissues in tortellini meat-filling coming from
four Italian commercial brands (Ghisleni, Stella, Radaelli, Mattiello, &
Scanziani, 2010). The filling quality was assessed by examining histological sections followed by evaluation of the percentage area of skeletal
muscle by a computerised image analysis system. They concluded that
this approach is a reliable tool to estimate the quality of meat filling in
terms of the amount of skeletal muscle and to identify small amounts
or traces of different animal tissues in processed meat products.

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Spectroscopy
The use of different optical measurements has been applied as
a rapid and non-destructive screening approach for discriminating
among the different meat species that can be present in foodstuffs.
Additional advantages of this approach would be the small sample
amounts required, together with minimal sample handling. On the
other hand, since the measured parameters are usually present in
meat samples and other food constituents regardless of the animal
species, it is difficult to get unambiguous results, so that it is necessary
to develop robust and highly discriminant data analysis models. Nearinfrared (NIR) spectroscopy combined with partial least squares discriminant analyses was employed by Tres, van der Veer, Perez-Marin,
van Ruth, and Garrido-Varo (2012) to authenticate the organic feed
used to nourish hens. According to them, spectral regions related to
the protein and fat content were among the most important to generate
the classification model. In another work, Sowoidnich and Kronfeldt
(2012) applied shifted excitation Raman difference spectroscopy
(SERDS) for in situ differentiation of beef, pork, chicken and turkey
fresh meat slices. In this work, principal component analysis was applied to spectral data obtained at two excitation wavelengths, allowing
a clear separation for the four species. However, such good discrimination results will be more difficult to obtain if we want to authenticate
foods containing mixes of several meat species. This is clearly illustrated
in the work carried out by Restaino, Fassio, and Cozzolino (2011), where
they applied NIR spectroscopy, together with chemometrics, in the
classification of meat patés according to the type of meat. Using this
technique in combination with stepwise linear discriminant analysis
(SLDA), they were able to correctly classify all patés containing either
100% beef or pork meat. However, for patés containing binary mixtures
of pork and beef meat, only 72% of them were correctly classified.
The overall conclusion was that the use of NIR in combination with
chemometric analysis can be a rapid initial screening method for revealing meat composition and detecting accidental contaminations or
fraudulent practices; however, this strategy should be combined with
more costly methods to prevent ambiguities and to assure an efficient
control all along the food chain. A similar conclusion can be obtained
from the results reported by Zhao, O'Donnell, and Downey (2013) at
the time to correctly detect offal adulteration in beefburgers.
Despite what it is stated, recent developments in techniques
based on NIR spectroscopy seem to be promising in detecting levels
of meat adulteration with non-declared animal species. Recently,
Kamruzzaman, Sun, ElMasry, and Allen (2013) reported the development of a technique based on near-infrared hyperspectral imaging
for detecting the level of adulteration in minced lamb with minced
pork meat. The advantage of this approach would be to integrate
spectroscopy and imaging in the same system in order to provide
both spectral and spatial information from the analysed samples.
This would allow us to detect a particular type of meat, including the
amount and its distribution throughout the analysed samples, something that is not possible with conventional spectroscopic techniques.
Authors selected four different wavelengths to build a multiple linear
regression (MLR) model showing a good prediction performance of
the level of pork adulteration. Interestingly, an image processing algorithm was developed to apply the MLR model to each pixel in the
image in order to see the distribution of the contaminating meat in
the sample (see Fig. 1). NIR hyperspectral imaging has also been applied
for its potential as a rapid and non-destructive technique capable to
assess meat freshness. Thus, partial least squares discriminant analysis
models (PLS-DA) of NIR reflectance spectra were carried out by
Barbin, Sun, and Su (2013) in order to distinguish between fresh
and frozen-then-thawed pork meat samples. A model based on the
most significant wavelengths allowed for reduced spectral data and
an overall correct classification of 100% for an independent set of
samples. NIR hyperspectral imaging has also recently been applied to
assess the microbial contamination of pork meat, with some promising
results (Barbin, ElMasry, Sun, Allen, & Morsy, 2013).

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M.Á. Sentandreu, E. Sentandreu / Food Research International 60 (2014) 19–29

Fig. 1. Hyperspectral imaging obtained by applying the multiple linear regression model developed by Kamruzzaman et al. (2013) using relevant near-infrared wavelengths to each pixel
of the spectral images (upper line). The obtained prediction maps showed the distribution of the adulteration of minced lamb with pork meat at different levels for 4 to 40% (bottom line).
Figure reproduced from the work of the mentioned authors.

Metabolomics
Metabolite analysis has been widely used by both research and
control laboratories as an efficient solution to address different
issues concerning the problem of meat authentication. The general
objective of the strategies that can be grouped herein would be to
identify and quantify the maximum number of low molecular weight
compounds contributing to discriminate between samples. Again,
the statistical data analysis and application of discriminant models
will be mandatory in order to highlight the sample differences.
Traditionally, metabolites have been analysed by the use of either
liquid (LC) or gas (GC) chromatography coupled to different detectors such as diode array, flame ionization (FID) or mass spectrometry
(MS). As an example, Gallardo, Narvaez-Rivas, Pablos, Jurado, and
Leon-Camacho (2012) performed the analysis, by using GC–FID,
of triacylglycerols extracted from subcutaneous fat of Iberian pigs
with the objective to discriminate between intensive and extensive
pig feeding systems. The same group also accomplished the discrimination of these two feeding systems though a first identification,
by using GC–MS, of six methyl sterols in subcutaneous fat, followed
by quantification of these chemical descriptors using GC–FID. They
applied several pattern recognition techniques in order to find the
best classification model, obtaining an overall classification rate
of almost 92% (Jurado et al., 2013). Despite the good results, this
illustrates the difficulty to get unambiguous results with these techniques based on what it is known as “metabolite profiling” approach.
Gas chromatography, and in general all chromatographic methods,
would display some drawbacks due to the fact that metabolites normally need to be previously extracted from samples. Also, the time required
for the analysis of each individual sample may be considerably long,
thus limiting the performance at the time to get results in control
laboratories. For that reason, other alternatives are being assayed and
developed for authentication purposes into the metabolomic approach.
Electronic nose has been recently used as an alternative to GC–MS to
undertake metabolite profiling of volatile compounds. It would display
several advantages, such as direct and rapid measurement of volatile
compounds from the sample headspace. This approach would not
allow the identification of individual compounds but the generation
of a characteristic “odour fingerprint” leading to discriminate, using
chemometric analysis, samples having different characteristics. In addition to speed, other advantages of the electronic nose arise from its
simplicity, friendly use, affordability and the condition to be a nondestructing method. On the other hand, the limit of detection would
be lower as compared to GC–MS. The use of an electronic nose in combination with several multivariate analysis methods has recently been
applied in detecting the presence of contaminating pork in minced
mutton meat (Tian, Wang, & Cui, 2013). In this work, authors were

able to correctly discriminate between different adulteration degrees,
ranging from 20 to 100% pork meat content in mixtures with lamb
meat. However, such a good level of discrimination in detecting
lower amounts of contaminating meat using this approach, for example
1–5%, would be considerably more difficult. Another recent and promising approach for the direct analysis of volatile compounds present in the
headspace of meat products is the use of proton transfer reaction mass
spectrometry coupled to a time-of-flight mass analyzer (PTR-ToF-MS).
It is based on the protonation of volatile compounds with proton affinity
higher than that of water. The use of a time-of-flight (ToF) mass analyzer offers several advantages, comparing to a simple quadrupole mass
spectrometer, at the time to detect the protonated compounds such as
enhanced mass resolution and faster spectra acquisition. Another
important characteristic of PTR-ToF-MS is its high sensitivity into the
low ppt region (Jordan et al., 2009). A good example illustrating the
use of this technology in the authentication of meat products is the
work carried out by del Pulgar et al. (2011), where they used PTRToF-MS for the rapid discrimination of dry cured hams coming from
four of the most important Italian and Spanish PDOs. The headspace
composition of each ham was analysed by direct injection without a
previous treatment or concentration, then obtaining a PTR-ToF mass
fingerprint characteristic of each ham type. Authors concluded, as illustrated in Fig. 2, that this approach can efficiently classify the different

Fig. 2. Score plots resulting from the principal component analysis of the PTR-ToF-MS
fingerprint obtained from the direct analysis of the headspace of Iberian (I), Parma (P),
San Daniele (SD) and Toscana (T) ham samples.
Figure reproduced from the work of del Pulgar et al. (2011).

M.Á. Sentandreu, E. Sentandreu / Food Research International 60 (2014) 19–29

hams according to both the geographical region and the production
process. In another work (del Pulgar et al., 2013), PTR-ToF-MS was
applied to the analysis of volatile compounds originated from Iberian
dry cured hams as a way to identify if pigs were fattened outdoor
by acorn and pasture (“Montanera” diet) or by concentrated feed
(“Campo” diet).
Innovative approaches in line to that of the electronic nose and PTRToF-MS have recently been reported for the metabolomic analysis of
non-volatile compounds in authentication studies. The group of Cajka,
Danhelova, Zachariasova, Riddellova, and Hajslova (2013) reported a
novel strategy consisting of direct analysis in real time (DART) ionization coupled to time-of-flight mass spectrometry (ToF MS) to efficiently
differentiate between chickens fed with chicken bone meal or not. This
is a fraudulent practice, since EU regulations do not authorize the use
of by-products to feed animals with proteins derived from the same
species. The extraction conditions were optimized in order to simultaneously obtain as many polar and non-polar compounds as possible.
Introduction of the extracted compounds was automated in order to reduce the analysis time of all ionisable compounds using DART-ToF MS.
The result is the rapid acquisition of a “metabolomic fingerprint” characteristic of each type of sample. As usual, multivariate data analysis was
finally applied for the correct discrimination of muscle samples from
chickens according to the type of diet. A similar philosophy was followed in the work of Gonzalez-Dominguez, Garcia-Barrera, and GomezAriza (2012) in the development of a rapid and efficient strategy to
assess the authenticity of Iberian dry-cured ham. In this case authors
undertook a direct infusion of dichloromethane/methanol extracts
obtained from ham intramuscular fat on a quadrupole/time-of-flight
(QToF) mass spectrometer. Tandem mass spectrometry (MS/MS)
using this instrument allowed obtaining characteristic intramuscular
fat fingerprints depending on the type of feeding (i. e. “Montanera” vs.
“Foodstuff diet”), given to the pigs. Iberian ham is a typical dry-cured
product of some regions of Spain known for its supreme quality. For
that reason, authentication of these products is a matter of high
economic incidence and, hence, it is not surprising to observe a rapid
and dynamic evolution of the metabolomic approaches assayed in this
field. This is also true for other cured meat products having a Protected
Designation of Origin around the world. As we have already seen
for volatile compounds, a key point of the innovations applied to
metabolomic analysis is reducing the complexity of sample preparation
prior to analysis. In the analysis of non-volatile metabolites, Osorio,
Moloney, Brennan, and Monahan (2012) reported the development
of a non-invasive metabolomic analysis using urine samples to authenticate the cattle production system depending on the feeding type. To do
that, urine samples from bovine animals having four different diets
along one year (pasture outdoors vs. barley concentrate indoors) were
analysed by nuclear magnetic resonance and multivariate data analysis.
The identification of the major discriminating peaks allowed them to
identify novel potential markers of the cattle production system
including creatinine, glucose, hippurate, pyruvate, phenylalanine
and phenylacetylglycine.
Targeted approaches: study of specific compounds
As already commented, the analytical strategies commented up to
now are frequently associated with an overall measurement of chemical
compounds, metabolites and/or image datasets, thus being necessary
to use powerful discriminant analysis models capable to establish
good classification rates. In some cases, as shown in some of the above
commented works, these models allow establishing a clear separation
between samples having different animal or geographical origin, chemical composition or processing conditions. But, unfortunately, such a
clear discrimination is not possible in all cases. This can be explained
from the fact that a particular animal meat type can display a large
natural variation due to multiple factors such as breed, sex, rearing
conditions or age/season at the time of slaughter, making the

23

comparison of results extremely complex and consequently affecting
reliability of results. An alternative to these approaches based on
overall measurements is to focus the analysis on a more defined
group of key biomarkers, capable to provide the necessary information
about the presence of a specific type of meat, tissue and/or adulterant. In
these targeted approaches, the detection of marker proteins, peptides
and/or amino acids has traditionally been used for this purpose.
Techniques not based on discrimination at sequence level
Electrophoretic and chromatographic methods. Both mono- and bidimensional protein electrophoresis have been used to reveal differences in the mobility of target proteins of the different meat species
(Montowska & Pospiech, 2011) or to discriminate between dry-cured
hams coming from different parts of Europe (Olias et al., 2006). However, they have some important limitations in terms of repeatability and
low discriminating power so that the obtained results can be ambiguous
and far from being clear and conclusive. In addition to this, the time
needed for sample preparation and analysis is not negligible. As an
alternative, capillary electrophoresis (CE) has also been assayed for
authentication purposes. Vallejo-Cordoba, Rodriguez-Ramirez, and
Gonzalez-Cordova (2010) used this approach to create electrophoretic
protein profiles capable to differentiate between bovine and ostrich
meat. As discrimination was mainly based on quantitative differences
of proteins common to both species, the ability of the technique for
the authentication of products containing mixes of meats would be
limited. Capillary electrophoresis has also been used as a strategy to
compare peptide profiles that would allow predicting the curing time
of Spanish dry cured hams (Lerma-Garcia, Herrero-Martinez, RamisRamos, Mongay-Fernandez, & Simo-Alfonso, 2009). Using a linear discriminant analysis model they were able to correctly classify hams in
three different curing times (6, 8 and 12 months). Authors also stated
that using a multiple linear regression model they were able to predict
the curing time with an average prediction error below 2.5%. In another
work, CE was used to determine the content of hydroxyproline in meat
products as an index of the collagen content (Mazorra-Manzano,
Torres-Llanez, Gonzalez-Cordova, & Vallejo-Cordoba, 2012). This is an
important issue in authenticity studies since the addition of collagen
or its hydrolysates is a common practice in the meat industry to
increase the protein content or water binding properties of meat products. However, the total content is limited by regulatory agencies in
processed meats, so that there is need for methods to accurately determine the collagen index. In this respect, liquid chromatography (LC)
coupled to electrochemical detection (EC) has also been used to determine the hydroxyproline content in meat products (Messia, Di Falco,
Panfili, & Marconi, 2008). Compared to other chromatographic approaches, the major advantage of the electrochemical detection would
be the direct analysis of peptides and amino acids without previous
derivatization. LC coupled to EC has also been used to specifically detect
ostrich meat and differentiate it from pork, beef and chicken meat
(Hung et al., 2011).
Immunoassays. Immunoassays have been widely used for meat
authentication purposes due to some important advantages such as
their easy implementation by non-specialised personnel, affordable
cost, high sensitivity and the possibility to process a high number
of samples in short times. All these characteristics make them suitable for routine use in food control laboratories. The performance
of the assay relies on the ability of the available antibodies to specifically detect the target protein/peptide characteristic of a particular
animal species, tissue or meat adulterant. In addition to meat
authenticity, immunoassays are of relevant importance in meat safety
because they constitute a rapid and efficient way to detect the contamination of meat and meat products either by pathogens, such as the case
of Salmonella in poultry meat (Chajecka-Wierzchowska, Zadernowska,
Klebukowska, & Laniewska-Trokenheim, 2012), or by illegal drugs,

24

M.Á. Sentandreu, E. Sentandreu / Food Research International 60 (2014) 19–29

such as the presence of fluoroquinonole residues in chicken meat (Liu
et al., 2013). Immunoassays have also proved to be useful in detecting
different types of tissues of the same species in meat products (Asensio,
Gonzalez, Garcia, & Martin, 2008), a fact that can have a relevant importance in terms of consumer's health. As an example, pork and beef kidney
are more prone to cause allergic responses followed by severe anaphylaxis than the meat of these two species itself (Morisset et al., 2012). This
highlights the importance to assure a correct labelling of meat products
in terms of the offal content. Problems of allergies in meat products can
also arise by the presence of either milk or egg proteins as part of the ingredients. Again, legislation must protect against the undeclared addition
of these protein sources.
Among the different immunological assays, the Enzyme Linked
Immunosorbent Assay (ELISA) is probably the most widely used
technique for authentication purposes. Additional information
about the use of ELISA in food authenticity can be found in the review
written by Asensio et al. (2008). Despite its many advantages, immunoassays are not exempted from some limitations such as the need for
specific antibodies. If antibodies are not highly specific of a particular
species and/or tissue, problems associated with cross-reactions can
arise, giving rise to false positive cases. This can be especially problematic at the time to differentiate between closely related species. As an
example, we have the case of chicken and turkey samples, for which
commercial ELISA kits normally identified these meat under the general
denomination of “poultry meat” (Giovannacci et al., 2004). Other limitations reported for immunoassays concerns the analysis of highly processed meat products, because aggressive conditions such as high
thermal treatments can alter the tertiary structure of proteins, thus negatively affecting their recognition by the antibody (Nakyinsige et al.,
2012). This can give rise to false negatives or to underestimated results
of the ingredient subjected to quantification. Some innovations have
recently been reported to overcome this problem with the production
of antibodies raised against thermostable proteins. This is the case of
osteocalcin, a tissue-specific protein of the extracellular bone matrix
that has been used as target antigen for the immunological detection
of meat and bone meal (MBM) used in farm animal feeding, a practice
strictly controlled nowadays by official regulations (Kreuz et al.,
2012). In the strategy reported by Kotoura et al. (2012) they were
able to specifically determine the content of beef meat in different
model and commercial processed foods by developing a sandwich
ELISA comprising two types of monoclonal antibodies, one type against
denatured beef myoglobin and a second one raised against an amino
acid sequence unique to beef myoglobin. By this way, in addition to
determine the beef meat content independently of the processing
conditions, the assay proved to be highly specific for bovine species,
showing no cross-reaction neither with pork and chicken meat nor
with other food proteins such as those coming from cow's milk, egg,
wheat and peanuts.
Techniques based on discrimination at sequence level
Methods based on DNA analysis. Analytical techniques based on the analysis of DNA have rapidly evolved during the last years as an alternative
to overcome the limitations already commented for the approaches
based on protein analysis and other target compounds. One of the
main advantages of DNA-based methodologies, and in particular of
those based on the polymerase chain reaction (PCR), is their high discriminating power. This is because identification is made at sequence
level of specific DNA fragments that are unique of a particular animal
or plant species. This feature will allow us to obtain unambiguous
results, making the assays efficient and reliable. Another important
advantage is their high level of sensitivity, being feasible to detect 0.1%
or even lower levels of a particular meat species in a food product
(Natonek-Wisniewska, Krzyscin, & Piestrzynska-Kajtoch, 2013). We
could think that such a low level of detection is not really necessary at
the time to detect additions of undeclared meats because fraud is

normally made with the objective to get additional economic gain and
consequently much higher amounts, for example above 10%, would be
expected to be found. However, contamination with trace amounts of
non-declared meats can occur when different animal species are being
processed using the same machinery in a meat industry (Rojas et al.,
2011). This particular case of adulteration can be of relevant importance
for some religious groups such as the Muslim population, where
the presence of any amount of pork meat in a food product will make
the product lose its Halal status, rendering it unacceptable for this
population (Mohamad, El Sheikha, Mustafa, & Mokhtar, 2013). For
these scenarios, highly sensitive methodologies such as PCR or immunoassays would be the only way to certify the absence of any traces of
a particular type of meat in foods.
The above commented characteristics make DNA analysis the method of choice for differentiating between closely related species. As an example, a real-time PCR assay has been developed for differentiating
between chicken and turkey meat (Kesmen, Yetiman, Sahin, & Yetim,
2012), and between horse and donkey meat (Kesmen, Gulluce, Sahin,
& Yetim, 2009). In another work, Fajardo et al. (2008b) carried out the
design of cervid-specific primers to develop real-time PCR assays capable to differentiate between red deer, fallow deer and roe deer in meat
mixtures. As we can see, the resolving power of PCR approach could
solve the problem of discriminating between closely related species or
even between different breeds of the same species (Fajardo et al.,
2008a). This is an issue of major relevance at the time to authenticate
the meat content of traditional and regional foods, since during the processing of these products specific animal breeds characteristic of a particular geographic area are normally employed. Despite the successful
commented examples this is a complex question that is far to be solved,
but undoubtedly the genetic approach constitutes one of the most
promising alternatives at the time to authenticate individual animal
breeds (Montowska & Pospiech, 2012).
Genetic methods can also show important limitations, especially in
the analysis of processed meat products. Foods are very complex matrices and this complicates the development of standardized extraction
protocols, thus needing to optimize them for each particular case in
order to assure that reproducible amounts of DNA are being extracted
from each sample (Lopez-Andreo, Aldeguer, Guillen, Gabaldon, &
Puyet, 2012). The aggressive conditions frequently used during the processing of meat products can cause the disruption of DNA due to high
temperatures, pH changes or the disruption of the cellular integrity
and the liberation of DNAases, for example. The final consequence is
that the amount of DNA present in the product would not reflect
the real amount of the source material in the product, impairing quantitative measurements (Primrose et al., 2010). Another negative consequence of food processing on DNA degradation would be the reduction
in length of DNA fragments that can be used to implement PCR assays,
increasing the possibilities of cross-reactions with other meat species
(Hird et al., 2006). Another important aspect of quantitative PCR is the
selection of the target genes used for amplification. In order to obtain
reproducible quantitative measurements, single-copy DNA should be
employed. For this reason, nuclear DNA would be preferred. Mitochondrial DNA, as it is present in multiple and varying copies depending on
the type of tissue, would pose more problems for accurate and reproducible measurements. On the other side, however, analyses using mitochondrial DNA would have a considerable lower limit of detection,
in addition to the fact that it has a better survival rate in highly processed foods (Mohamad et al., 2013). Another problem of using singlecopy nuclear DNA deals with the fact that it is more difficult to find
amplifiable regions specific of a particular meat species, increasing the
problems of cross-reactivity (Ballin, Vogensen, & Karlsson, 2012).
In that respect, innovations can be observed in recent reports to
overcome some of these drawbacks. In the work of Soares, Amaral,
Oliveira, and Mafra (2013), they developed a real-time PCR approach
for the quantitative detection of pork meat in processed meat products.
The strategy to obtain reliable quantitative measurements included the

M.Á. Sentandreu, E. Sentandreu / Food Research International 60 (2014) 19–29

construction of a calibration curve with binary mixtures containing
known amounts of pork meat in poultry meat. Authors highlighted
the importance to have this curve in order to control variations in
DNA extraction and efficiency of amplification. Sensitivity and specificity of the assay for porcine species were achieved by amplification of a
DNA fragment from mitochondrial cytochrome c gene previously
reported by Dooley, Paine, Garrett, and Brown (2004). Despite its
short length (149 base pairs), the selected fragment showed no crossreaction with other animal species, thus being adequate for amplification in processed samples. With the objective to obtain reliable quantitative measurements, authors also amplified a selected fragment from
nuclear 18S rRNA as endogenous control (previously reported by
Fajardo et al., 2008b) to verify if amplification variations found with
the species-specific cytochrome c fragment were due to differences in
the pork meat content or to other factors related to meat processing
and/or the amount and quality of extracted DNA. The use of such an
endogenous control allows controlling these variations.
The proteomic approach: analysis of proteins and peptides using
mass spectrometry. The possibility to apply mass spectrometry (MS)
analysis for determining the molecular weight and amino acid sequence
of peptides and proteins has been of relevant importance in biological
research. It means a different way to undertake the identification
of these biomolecules with respect to the classical approach using
N-terminal sequencing based on Edman degradation. Modern
Proteomics, also known as the “Postgenomic Revolution”, has been
possible thanks to the development of soft ionization techniques
such as MALDI (Matrix-Assisted Laser Desorption Ionisation) and ESI
(Electrospray Ionisation). MALDI and ESI allow the rapid ionization of
peptides and proteins prior the MS analysis, outlining a new concept
in their use as accurate and reliable biomarkers capable to determine
the composition of meat and meat products for meat authentication
purposes (Sentandreu & Sentandreu, 2011). The achieved discrimination power can be comparable to methods based on DNA analysis,
since the peptide sequences used as biomarkers are specific for a particular animal or plant species. However, authentication methods based
on peptide identification by MS would have the additional advantage
to differentiate between tissues of the same species when targeting
peptide sequences of tissue-specific proteins. An example of this can
be found in the work carried out by Balizs et al. (2011), where they
were able to detect and differentiate the presence of meat and
bone meal of bovine and porcine origin through the identification of
species-specific tryptic peptides derived from osteocalcin, a protein
constituent of calcified bone. As we have already seen, other approaches
such as histology (Prayson et al., 2008) have also been employed to

Peptide

Mass

Position

25

detect meat and bone meal, but in that case discrimination between
species was not possible.
The proteomic approach has great potential in terms of robustness
and reliability at the time to authenticate highly processed meats
where other techniques have shown to have more limitations. For
these products, the extraction of proteins and peptides is more
amenable as compared to DNA extraction procedures, facilitating
the development of standardized extraction protocols. In addition
to this, the primary amino acid sequence of peptides is more resistant to processing conditions than short DNA sequences, thus offering the possibility to develop reliable quantitative determinations.
Modern mass spectrometers feature great performance in terms of
mass accuracy and sensitivity, which greatly helps to detect low
amounts of contaminating meats and/or other undeclared ingredients
in meat products. However, there are also some limitations that need
to be surpassed such as the high cost of modern MS equipments
and the need for skilled operators. For that reason, research aiming at
developing MS methodologies should take in mind the use of a routine
and affordable technology, adequate for control laboratories.
Although the use of Proteomics in meat authentication studies is still
rather limited, some representative examples can be found in the literature highlighting the potential of this approach in Meat Science. Mass
spectrometry has been used to evaluate the potential allergenicity of
meat coming from genetically modified chicken (Nakamura et al.,
2010). In this work, serological analysis using western blot was used
to detect several IgE-binding proteins in chicken meat. Then, the identity of the immunoreactive proteins was elucidated by MALDI-ToF/ToF
MS. Differences in the expression of these proteins were evaluated by
two-dimensional difference gel electrophoresis (2D-DIGE), concluding
that the allergenic potential did not change in GM chicken with respect
to its non-modified counterpart.
The use of mass spectrometry in meat species identification was
already proposed by Taylor, Linforth, Weir, Hutton, & Green, 1993
using as discriminant criterion the mass differences existing between
myoglobins and haemoglobins of the different meat species. The work
was carried out using solutions of pure proteins, highlighting that the
situation with real animal samples would be a more challenging question. Espinoza, Lindley, Gordon, Ekhoff, and Kirms (1999) used the
same approach working with real blood samples, being able to identify
a wide variety of animal species relying on the mass differences of
haemoglobin α- and β-chains. Even if authors adequately discriminated
most of the analysed samples, a small percentage (14%) yielded ambiguous identifications because of interspecies overlap of haemoglobin
mass values. A solution for this would be to increase the resolving
power of the proteomic approach by using species-specific peptide

Sequence

Parent protein

Species

A

759.98 (2+) 120-134

MYG_HORSE Equus caballus

B

774.97 (2+) 120-134

MYG_BOVIN

Bos taurus

Fig. 3. Sequence alignment of horse and bovine myoglobins. Amino acid differences between the two sequences are indicated in green (horse) and orange (bovine) colours. Blue sequences
correspond to the identified species-specific biomarker peptides generated after trypsin digestion of the proteins and sequenced by tandem mass spectrometry (MS/MS). The table is a
summary of the main characteristics of these marker peptides. Amino acids differing between horse and beef species are underlined (Palés et al., 2013).

26

M.Á. Sentandreu, E. Sentandreu / Food Research International 60 (2014) 19–29

0.5 % chicken
99.5 % pork

Protein extraction

OFFGEL fractionation
Trypsin digestion

Myosin Light Chain 3

LC-ESI-MS/MS

A

Selected Ion Monitoring for peptide ALGQNPTNAEINK (m/z 685.53 2+)

B
84.1 min

Fig. 4. Schematic summary of the peptidomic approach developed by Sentandreu et al. (2010) for detecting the presence of chicken meat in mixes with other meats. The method was developed
considering the model case of a binary mixture of chicken and pork meat. The method proved to be robust and reliable, being able to detect the presence of 0.5% contaminating chicken in a
mixture with pork meat indistinctively of being raw or highly cooked (1 h, 180 °C) meat samples. In the diagram, only the MS detection of one of the chicken marker peptides is presented.

sequences as discriminant criterion, instead of the molecular mass
determinations of intact proteins. This strategy has recently been
followed by Palés et al. (2013) in the development of a MS method to

differentiate horse from beef meat in foods with high confidence.
Myoglobin was used as the target protein for the generation, by trypsin
hydrolysis, of equine and bovine specific peptide markers whose

M.Á. Sentandreu, E. Sentandreu / Food Research International 60 (2014) 19–29

Picomol of peptide ALGQNPTNAEINK

sequence was elucidated by tandem mass spectrometry (MS/MS).
Two peptides, corresponding to position 120–134 of the myoglobin
sequence, were identified as specific of each one of these animal
species, allowing for unambiguous results (Fig. 3).
It is worth noting that success in the reported results from the
above commented works was largely dependent on the fact that
hemoproteins (haemoglobin and myoglobins) had been previously
characterized from the biochemical point of view. This is going to
be one of the main requirements at the time to select the target proteins
for species identification using MS. Information about molecular
weight, together with the amino acid sequence of a particular protein,
has preferably to be available for the different species of interest; otherwise, the work to characterize the protein/peptide biomarkers for discriminating between samples will become considerably harder.
In the work reported by von Bargen, Dojahn, Waidelich, Humpf, and
Brockmeyer (2013), peptide biomarkers were also used to develop a
sensitive multiple reaction monitoring (MRM) mass spectrometry
approach capable to detect low amounts of horse and pork meat
in beef samples. According to authors, the method could be applied in
routine control laboratories equipped with triple–quadrupole instruments. In this case, the marker peptides selected for developing the
MRM-based method derived from the trypsin digestion of troponin T
and myosin heavy chain muscle proteins. The proteomic approach has
also been used by Sentandreu, Fraser, Halket, Patel, and Bramley
(2010) to undertake the specific detection of chicken meat in foodstuffs.
In this research, the two peptide biomarkers used for the unambiguous
identification of chicken species were generated from the trypsin
hydrolysis of myosin light chain 3. The method proved to be robust
and reliable since heat treatment did not affect the detection of peptides, thus allowing indistinct analysis of both raw and cooked meat
samples. A schematic diagram of this procedure is illustrated in Fig. 4.
Furthermore, sensitivity of the developed procedure was rather high,
being able to detect the presence of 0.5% chicken in a mixture with
pork meat. Finally, as it is shown in Fig. 5, the use stable isotopelabelled marker peptides as internal standards enabled this method
for quantitative measurements.
The robustness and high discriminating power of peptide biomarkers
and MS/MS identification in authentication studies are clearly illustrated
in the work reported by Buckley et al. (2010). These authors described
a method based on the identification of collagen peptides capable to
discriminate between sheep and goat species. The samples used in this
study were archaeological bones, and despite the high sequence

27

homology of the collagen proteins, differing amino acids were
found for sheep and goat at two positions of the protein chain. This
illustrates the higher resistance of the primary amino acid sequence
of peptides as compared to DNA sequences, supporting the potential
of the peptidomic approach in the authentication studies of highly
processed meats.

Concluding remarks: the art to be authentic
The problem of meat authenticity may imply quite many different
illegal procedures, but also accidental mislabelling and problems associated with cross-contamination in processing plants sharing common
machinery for the production of different meat products. Research in
this field is quite dynamic as it can be deducted from all the techniques
and innovations that have been reviewed here. Even if it is true that not
all the techniques have the same characteristics in terms of robustness,
reliability and sensitivity, we should keep in mind the idea that there
is no perfect analytical tool capable to provide an answer for all the
problems we can encounter at the time to reveal the composition
of meat and meat products. We have a wide variety of different
approaches that would be complementary between them. The rapid
and non-invasive techniques such as those based on spectroscopy analysis, for example, would be the method of choice in production plants as
screening methods capable to quickly provide information about food
composition and potential frauds. When positive cases of adulteration
or ambiguous results are obtained, we will require working with other
invasive and slower techniques but offering more reliable and unambiguous results such as the immunoassays, genetic techniques or methods
based on mass spectrometry analysis, for example. At the end, the
question is to assure authenticity, protecting consumer's health and
rights above all.
Acknowledgements

30

Financial support of projects AGL2012-32146 from the Spanish
Ministry of Economy and Competitiveness and GV/2010/071 from
Generalitat Valenciana are fully acknowledged. Part of the work carried
out by the authors and revised in this manuscript was possible thanks to
the financial support of the UK Food Standards Agency (project Q0114).
Our sincere gratitude also to P. Bramley, J. Halket, P. Fraser, and R. Patel
(School of Biological Sciences, Royal Holloway, University of London)
for their intellectual input during the FSA project and the good time
spent together in the UK: “Good, good, chaps!”.

25

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y= 2.7523x

20

R2=0.9921
15
10
5
0
0

1

2

3

4

5

6

7

8

9

10

% chicken in pork meat
Fig. 5. Quantitative assay for calculating the presence of chicken meat in different mixtures
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ALGQNPTNAEINK was added to samples as internal standard. As it can be observed,
there is a good linearity between the amount of the detected marker peptide and the
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