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Open AccessReview

Predicting the Quality of Meat: Myth or Reality?

UMR Biologie des Oiseaux et Aviculture, INRA, Université de Tours, 37380 Nouzilly, France
UMR Herbivores, INRA, VetAgro Sup, Theix, 63122 Saint-Genès Champanelle, France
UMR Physiologie, Environnement et Génétique pour l’Animal et les Systèmes d’Élevage, INRA, AgroCampus Ouest, 35590 Saint-Gilles, France
Laboratoire de Physiologie et Génomique des poissons, INRA, 35000 Rennes, France
Institut du porc, La motte au Vicomte, 35651 Le Rheu, CEDEX, France
Institut de l’Elevage, Maison Régionale de l’Agriculture—Nouvelle Aquitaine, 87000 Limoges, France
Author to whom correspondence should be addressed.
Foods 2019, 8(10), 436;
Received: 6 September 2019 / Revised: 16 September 2019 / Accepted: 20 September 2019 / Published: 24 September 2019
This review is aimed at providing an overview of recent advances made in the field of meat quality prediction, particularly in Europe. The different methods used in research labs or by the production sectors for the development of equations and tools based on different types of biological (genomic or phenotypic) or physical (spectroscopy) markers are discussed. Through the various examples, it appears that although biological markers have been identified, quality parameters go through a complex determinism process. This makes the development of generic molecular tests even more difficult. However, in recent years, progress in the development of predictive tools has benefited from technological breakthroughs in genomics, proteomics, and metabolomics. Concerning spectroscopy, the most significant progress was achieved using near-infrared spectroscopy (NIRS) to predict the composition and nutritional value of meats. However, predicting the functional properties of meats using this method—mainly, the sensorial quality—is more difficult. Finally, the example of the MSA (Meat Standards Australia) phenotypic model, which predicts the eating quality of beef based on a combination of upstream and downstream data, is described. Its benefit for the beef industry has been extensively demonstrated in Australia, and its generic performance has already been proven in several countries. View Full-Text
Keywords: meat; quality; prediction; biological marker; spectroscopy; phenotypic model meat; quality; prediction; biological marker; spectroscopy; phenotypic model
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Berri, C.; Picard, B.; Lebret, B.; Andueza, D.; Lefèvre, F.; Le Bihan-Duval, E.; Beauclercq, S.; Chartrin, P.; Vautier, A.; Legrand, I.; Hocquette, J.-F. Predicting the Quality of Meat: Myth or Reality? Foods 2019, 8, 436.

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