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Predicting the Quality of Meat: Myth or Reality?

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 o...

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Autores principales: Berri, Cécile, Picard, Brigitte, Lebret, Bénédicte, Andueza, Donato, Lefèvre, Florence, Le Bihan-Duval, Elisabeth, Beauclercq, Stéphane, Chartrin, Pascal, Vautier, Antoine, Legrand, Isabelle, Hocquette, Jean-François
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6836130/
https://www.ncbi.nlm.nih.gov/pubmed/31554284
http://dx.doi.org/10.3390/foods8100436
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author Berri, Cécile
Picard, Brigitte
Lebret, Bénédicte
Andueza, Donato
Lefèvre, Florence
Le Bihan-Duval, Elisabeth
Beauclercq, Stéphane
Chartrin, Pascal
Vautier, Antoine
Legrand, Isabelle
Hocquette, Jean-François
author_facet Berri, Cécile
Picard, Brigitte
Lebret, Bénédicte
Andueza, Donato
Lefèvre, Florence
Le Bihan-Duval, Elisabeth
Beauclercq, Stéphane
Chartrin, Pascal
Vautier, Antoine
Legrand, Isabelle
Hocquette, Jean-François
author_sort Berri, Cécile
collection PubMed
description 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.
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spelling pubmed-68361302019-11-25 Predicting the Quality of Meat: Myth or Reality? Berri, Cécile Picard, Brigitte Lebret, Bénédicte Andueza, Donato Lefèvre, Florence Le Bihan-Duval, Elisabeth Beauclercq, Stéphane Chartrin, Pascal Vautier, Antoine Legrand, Isabelle Hocquette, Jean-François Foods Review 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. MDPI 2019-09-24 /pmc/articles/PMC6836130/ /pubmed/31554284 http://dx.doi.org/10.3390/foods8100436 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Berri, Cécile
Picard, Brigitte
Lebret, Bénédicte
Andueza, Donato
Lefèvre, Florence
Le Bihan-Duval, Elisabeth
Beauclercq, Stéphane
Chartrin, Pascal
Vautier, Antoine
Legrand, Isabelle
Hocquette, Jean-François
Predicting the Quality of Meat: Myth or Reality?
title Predicting the Quality of Meat: Myth or Reality?
title_full Predicting the Quality of Meat: Myth or Reality?
title_fullStr Predicting the Quality of Meat: Myth or Reality?
title_full_unstemmed Predicting the Quality of Meat: Myth or Reality?
title_short Predicting the Quality of Meat: Myth or Reality?
title_sort predicting the quality of meat: myth or reality?
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6836130/
https://www.ncbi.nlm.nih.gov/pubmed/31554284
http://dx.doi.org/10.3390/foods8100436
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