Prédire la qualité des viandes : mythe ou réalité ? Etat des lieux des avancées récentes réalisées dans le domaine de la prédiction des qualités des viandes ; réflexion sur les perspectives d’application
Identifieur interne : 001399 ( Main/Exploration ); précédent : 001398; suivant : 001400Prédire la qualité des viandes : mythe ou réalité ? Etat des lieux des avancées récentes réalisées dans le domaine de la prédiction des qualités des viandes ; réflexion sur les perspectives d’application
Auteurs : Cécile Berri [France] ; Brigitte Picard [France] ; Bénédicte Lebret [France] ; Jesus Donato Andueza Urra [France] ; Antoine Vautier [France] ; Pascal Chartrin [France] ; Stéphane Beauclercq [France] ; Florence Lefèvre [France] ; Isabelle Legrand [France] ; Jean-François Hocquette [France]Source :
- Viandes et Produits Carnés [ 0241-0389 ] ; 2016.
Descripteurs français
English descriptors
Abstract
This review was aimed at providing an overview of recent advancements obtained in the field of meat quality prediction. The differentmethods used in the production sectors for the development of equations and the tools used based on different types of biological markers(genomic or phenotypic) or physical (spectroscopy) are discussed. Through the different examples that are presented, it appears that theidentification of biological markers is confronted with the complex determinism of quality parameters. This makes the development of genericmolecular tests to be used on the field even more difficult. However, in recent years, progress has been made, benefitting from genomics,proteomics and metabolomics technological developments. The first equations that predict the sensorial quality and the technological potentialof meat hint to possible applications in the near future. Concerning spectroscopy, the main results were obtained using Near Infrared Spectroscopy(NIR) with developments obtained for the prediction of the composition and nutritional value of meats. The prediction of the technologicalpotential of meats using this method and mainly the sensorial quality is, however, more difficult. Finally, the example of the MSA (« MeatStandards Australia ») phenotypic model which predicts the sensorial quality of bovine meat based on a combination of upstream and downstreamdata and whose added-value for the sector has been identified in Australia, presents a genericness that has already been proven in severalcountries.
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Le document en format XML
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<orgName type="acronym">UMRH 1213 Herbivores</orgName>
<desc> <address> <addrLine>INRA / Site de Theix / 63122 Saint-Genès-Champanelle</addrLine>
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<orgName type="acronym">INRA</orgName>
<desc> <address> <country key="FR"></country>
</address>
<ref type="url">http://www.inra.fr</ref>
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</org>
</tutelle>
<tutelle name="UMR1213" active="#struct-415469" type="direct"><org type="institution" xml:id="struct-415469" status="VALID"> <orgName>Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement</orgName>
<orgName type="acronym">AgroSup Dijon</orgName>
<date type="start">2009-03-01</date>
<desc> <address> <addrLine>26 Boulevard du Dr Petitjean - BP 87999 - 21079 Dijon cedex</addrLine>
<country key="FR"></country>
</address>
<ref type="url">http://www.agrosupdijon.fr/</ref>
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</org>
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<tutelle name="UMR1213" active="#struct-301767" type="direct"><org type="institution" xml:id="struct-301767" status="VALID"> <orgName>VetAgro Sup</orgName>
<desc> <address> <country key="FR"></country>
</address>
</desc>
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</hal:affiliation>
<country>France</country>
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<author><name sortKey="Vautier, Antoine" sort="Vautier, Antoine" uniqKey="Vautier A" first="Antoine" last="Vautier">Antoine Vautier</name>
<affiliation wicri:level="1"><hal:affiliation type="institution" xml:id="struct-326361" status="INCOMING"> <orgName>Institut du Porc</orgName>
<desc> <address> <country key="FR"></country>
</address>
</desc>
</hal:affiliation>
<country>France</country>
</affiliation>
</author>
<author><name sortKey="Chartrin, Pascal" sort="Chartrin, Pascal" uniqKey="Chartrin P" first="Pascal" last="Chartrin">Pascal Chartrin</name>
<affiliation wicri:level="1"><hal:affiliation type="laboratory" xml:id="struct-37692" status="VALID"> <orgName>Recherches Avicoles</orgName>
<orgName type="acronym">SRA</orgName>
<desc> <address> <country key="FR"></country>
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</desc>
<listRelation> <relation name="UR0083" active="#struct-92114" type="direct"></relation>
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<orgName type="acronym">INRA</orgName>
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</address>
<ref type="url">http://www.inra.fr</ref>
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</org>
</tutelle>
</tutelles>
</hal:affiliation>
<country>France</country>
</affiliation>
</author>
<author><name sortKey="Beauclercq, Stephane" sort="Beauclercq, Stephane" uniqKey="Beauclercq S" first="Stéphane" last="Beauclercq">Stéphane Beauclercq</name>
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<orgName type="acronym">SRA</orgName>
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<orgName type="acronym">INRA</orgName>
<desc> <address> <country key="FR"></country>
</address>
<ref type="url">http://www.inra.fr</ref>
</desc>
</org>
</tutelle>
</tutelles>
</hal:affiliation>
<country>France</country>
</affiliation>
</author>
<author><name sortKey="Lefevre, Florence" sort="Lefevre, Florence" uniqKey="Lefevre F" first="Florence" last="Lefèvre">Florence Lefèvre</name>
<affiliation wicri:level="1"><hal:affiliation type="laboratory" xml:id="struct-187317" status="VALID"> <orgName>Laboratoire de Physiologie et Génomique des Poissons</orgName>
<orgName type="acronym">LPGP</orgName>
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</address>
<ref type="url">http://www.rennes.inra.fr/lpgp</ref>
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<tutelle active="#struct-453207" type="direct"><org type="institution" xml:id="struct-453207" status="VALID"> <orgName>Structure Fédérative de Recherche en Biologie et Santé de Rennes </orgName>
<orgName type="acronym"> Biosit : Biologie - Santé - Innovation Technologique </orgName>
<desc> <address> <addrLine>Université Rennes 1 - Campus Santé Villejean - 2, avenue Professeur Léon Bernard 35043 Rennes cedex</addrLine>
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</address>
</desc>
</org>
</tutelle>
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<country>France</country>
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</author>
<author><name sortKey="Legrand, Isabelle" sort="Legrand, Isabelle" uniqKey="Legrand I" first="Isabelle" last="Legrand">Isabelle Legrand</name>
<affiliation wicri:level="1"><hal:affiliation type="laboratory" xml:id="struct-518754" status="INCOMING"> <orgName>Service Qualité des viandes</orgName>
<desc> <address> <country key="FR"></country>
</address>
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<desc> <address> <country key="FR"></country>
</address>
</desc>
</org>
</tutelle>
</tutelles>
</hal:affiliation>
<country>France</country>
</affiliation>
</author>
<author><name sortKey="Hocquette, Jean Francois" sort="Hocquette, Jean Francois" uniqKey="Hocquette J" first="Jean-François" last="Hocquette">Jean-François Hocquette</name>
<affiliation wicri:level="1"><hal:affiliation type="laboratory" xml:id="struct-37762" status="VALID"> <orgName>Unité Mixte de Recherches sur les Herbivores</orgName>
<orgName type="acronym">UMRH 1213 Herbivores</orgName>
<desc> <address> <addrLine>INRA / Site de Theix / 63122 Saint-Genès-Champanelle</addrLine>
<country key="FR"></country>
</address>
<ref type="url">http://umrh-bioinfo.clermont.inra.fr/Intranet/web/UMRH</ref>
</desc>
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<tutelles><tutelle name="UMR1213" active="#struct-92114" type="direct"><org type="institution" xml:id="struct-92114" status="VALID"> <orgName>Institut National de la Recherche Agronomique</orgName>
<orgName type="acronym">INRA</orgName>
<desc> <address> <country key="FR"></country>
</address>
<ref type="url">http://www.inra.fr</ref>
</desc>
</org>
</tutelle>
<tutelle name="UMR1213" active="#struct-415469" type="direct"><org type="institution" xml:id="struct-415469" status="VALID"> <orgName>Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement</orgName>
<orgName type="acronym">AgroSup Dijon</orgName>
<date type="start">2009-03-01</date>
<desc> <address> <addrLine>26 Boulevard du Dr Petitjean - BP 87999 - 21079 Dijon cedex</addrLine>
<country key="FR"></country>
</address>
<ref type="url">http://www.agrosupdijon.fr/</ref>
</desc>
</org>
</tutelle>
<tutelle name="UMR1213" active="#struct-301767" type="direct"><org type="institution" xml:id="struct-301767" status="VALID"> <orgName>VetAgro Sup</orgName>
<desc> <address> <country key="FR"></country>
</address>
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</hal:affiliation>
<country>France</country>
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</author>
</analytic>
<series><title level="j">Viandes et Produits Carnés</title>
<idno type="ISSN">0241-0389</idno>
<imprint><date type="datePub">2016</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><textClass><keywords scheme="mix" xml:lang="en"><term>marqueur biologique</term>
<term>meat</term>
<term>modèle phénotypique</term>
<term>prédiction</term>
<term>qualité</term>
<term>spectroscopie</term>
</keywords>
<keywords scheme="mix" xml:lang="fr"><term>perspective avancee</term>
<term>perspective d'application</term>
<term>produit carné</term>
<term>qualité de la viande</term>
<term>viande</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">This review was aimed at providing an overview of recent advancements obtained in the field of meat quality prediction. The differentmethods used in the production sectors for the development of equations and the tools used based on different types of biological markers(genomic or phenotypic) or physical (spectroscopy) are discussed. Through the different examples that are presented, it appears that theidentification of biological markers is confronted with the complex determinism of quality parameters. This makes the development of genericmolecular tests to be used on the field even more difficult. However, in recent years, progress has been made, benefitting from genomics,proteomics and metabolomics technological developments. The first equations that predict the sensorial quality and the technological potentialof meat hint to possible applications in the near future. Concerning spectroscopy, the main results were obtained using Near Infrared Spectroscopy(NIR) with developments obtained for the prediction of the composition and nutritional value of meats. The prediction of the technologicalpotential of meats using this method and mainly the sensorial quality is, however, more difficult. Finally, the example of the MSA (« MeatStandards Australia ») phenotypic model which predicts the sensorial quality of bovine meat based on a combination of upstream and downstreamdata and whose added-value for the sector has been identified in Australia, presents a genericness that has already been proven in severalcountries.</div>
</front>
</TEI>
<affiliations><list><country><li>France</li>
</country>
</list>
<tree><country name="France"><noRegion><name sortKey="Berri, Cecile" sort="Berri, Cecile" uniqKey="Berri C" first="Cécile" last="Berri">Cécile Berri</name>
</noRegion>
<name sortKey="Andueza Urra, Jesus Donato" sort="Andueza Urra, Jesus Donato" uniqKey="Andueza Urra J" first="Jesus Donato" last="Andueza Urra">Jesus Donato Andueza Urra</name>
<name sortKey="Beauclercq, Stephane" sort="Beauclercq, Stephane" uniqKey="Beauclercq S" first="Stéphane" last="Beauclercq">Stéphane Beauclercq</name>
<name sortKey="Chartrin, Pascal" sort="Chartrin, Pascal" uniqKey="Chartrin P" first="Pascal" last="Chartrin">Pascal Chartrin</name>
<name sortKey="Hocquette, Jean Francois" sort="Hocquette, Jean Francois" uniqKey="Hocquette J" first="Jean-François" last="Hocquette">Jean-François Hocquette</name>
<name sortKey="Lebret, Benedicte" sort="Lebret, Benedicte" uniqKey="Lebret B" first="Bénédicte" last="Lebret">Bénédicte Lebret</name>
<name sortKey="Lefevre, Florence" sort="Lefevre, Florence" uniqKey="Lefevre F" first="Florence" last="Lefèvre">Florence Lefèvre</name>
<name sortKey="Legrand, Isabelle" sort="Legrand, Isabelle" uniqKey="Legrand I" first="Isabelle" last="Legrand">Isabelle Legrand</name>
<name sortKey="Picard, Brigitte" sort="Picard, Brigitte" uniqKey="Picard B" first="Brigitte" last="Picard">Brigitte Picard</name>
<name sortKey="Vautier, Antoine" sort="Vautier, Antoine" uniqKey="Vautier A" first="Antoine" last="Vautier">Antoine Vautier</name>
</country>
</tree>
</affiliations>
</record>
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