Modelling of beef sensory quality for a better prediction of palatability.
Identifieur interne : 001462 ( Ncbi/Checkpoint ); précédent : 001461; suivant : 001463Modelling of beef sensory quality for a better prediction of palatability.
Auteurs : Jean-François Hocquette [France] ; Lynn Van Wezemael [Belgique] ; Sghaier Chriki [France] ; Isabelle Legrand [France] ; Wim Verbeke [Belgique] ; Linda Farmer [Royaume-Uni] ; Nigel D. Scollan [Royaume-Uni] ; Rod Polkinghorne [Australie] ; Rune R Dbotten [Norvège] ; Paul Allen [Irlande (pays)] ; David W. Pethick [Australie]Source :
- Meat science [ 1873-4138 ] ; 2014.
Descripteurs français
- KwdFr :
- MESH :
- analyse : Viande.
- normes : Viande.
- Animaux, Australie, Bovins, Contrainte mécanique, Contrôle de qualité, Europe, Goût, Humains, Modèles biologiques, Muscles.
- Wicri :
- geographic : Australie.
English descriptors
- KwdEn :
- MESH :
- geographic : Australia, Europe.
- analysis : Meat.
- standards : Meat.
- Animals, Cattle, Humans, Models, Biological, Muscles, Quality Control, Stress, Mechanical, Taste.
Abstract
Despite efforts by the industry to control the eating quality of beef, there remains a high level of variability in palatability, which is one reason for consumer dissatisfaction. In Europe, there is still no reliable on-line tool to predict beef quality and deliver consistent quality beef to consumers. Beef quality traits depend in part on the physical and chemical properties of the muscles. The determination of these properties (known as muscle profiling) will allow for more informed decisions to be made in the selection of individual muscles for the production of value-added products. Therefore, scientists and professional partners of the ProSafeBeef project have brought together all the data they have accumulated over 20 years. The resulting BIF-Beef (Integrated and Functional Biology of Beef) data warehouse contains available data of animal growth, carcass composition, muscle tissue characteristics and beef quality traits. This database is useful to determine the most important muscle characteristics associated with a high tenderness, a high flavour or generally a high quality. Another more consumer driven modelling tool was developed in Australia: the Meat Standards Australia (MSA) grading scheme that predicts beef quality for each individual muscle×specific cooking method combination using various information on the corresponding animals and post-slaughter processing factors. This system has also the potential to detect variability in quality within muscles. The MSA system proved to be effective in predicting beef palatability not only in Australia but also in many other countries. The results of the work conducted in Europe within the ProSafeBeef project indicate that it would be possible to manage a grading system in Europe similar to the MSA system. The combination of the different modelling approaches (namely muscle biochemistry and a MSA-like meat grading system adapted to the European market) is a promising area of research to improve the prediction of beef quality. In both approaches, the volume of data available not only provides statistically sound correlations between various factors and beef quality traits but also a better understanding of the variability of beef quality according to various criteria (breed, age, sex, pH, marbling etc.).
DOI: 10.1016/j.meatsci.2013.07.031
PubMed: 24035246
Affiliations:
- Australie, Belgique, France, Irlande (pays), Norvège, Royaume-Uni
- Auvergne (région administrative), Auvergne-Rhône-Alpes, Province de Flandre-Orientale, Région flamande
- Gand, Saint Genès Champanelle
- Université de Gand
Links toward previous steps (curation, corpus...)
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- to stream PubMed, to step Curation: 003572
- to stream PubMed, to step Checkpoint: 003572
- to stream Ncbi, to step Merge: 001462
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Links to Exploration step
pubmed:24035246Le document en format XML
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<front><div type="abstract" xml:lang="en">Despite efforts by the industry to control the eating quality of beef, there remains a high level of variability in palatability, which is one reason for consumer dissatisfaction. In Europe, there is still no reliable on-line tool to predict beef quality and deliver consistent quality beef to consumers. Beef quality traits depend in part on the physical and chemical properties of the muscles. The determination of these properties (known as muscle profiling) will allow for more informed decisions to be made in the selection of individual muscles for the production of value-added products. Therefore, scientists and professional partners of the ProSafeBeef project have brought together all the data they have accumulated over 20 years. The resulting BIF-Beef (Integrated and Functional Biology of Beef) data warehouse contains available data of animal growth, carcass composition, muscle tissue characteristics and beef quality traits. This database is useful to determine the most important muscle characteristics associated with a high tenderness, a high flavour or generally a high quality. Another more consumer driven modelling tool was developed in Australia: the Meat Standards Australia (MSA) grading scheme that predicts beef quality for each individual muscle×specific cooking method combination using various information on the corresponding animals and post-slaughter processing factors. This system has also the potential to detect variability in quality within muscles. The MSA system proved to be effective in predicting beef palatability not only in Australia but also in many other countries. The results of the work conducted in Europe within the ProSafeBeef project indicate that it would be possible to manage a grading system in Europe similar to the MSA system. The combination of the different modelling approaches (namely muscle biochemistry and a MSA-like meat grading system adapted to the European market) is a promising area of research to improve the prediction of beef quality. In both approaches, the volume of data available not only provides statistically sound correlations between various factors and beef quality traits but also a better understanding of the variability of beef quality according to various criteria (breed, age, sex, pH, marbling etc.).</div>
</front>
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<name sortKey="Verbeke, Wim" sort="Verbeke, Wim" uniqKey="Verbeke W" first="Wim" last="Verbeke">Wim Verbeke</name>
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<country name="Royaume-Uni"><noRegion><name sortKey="Farmer, Linda" sort="Farmer, Linda" uniqKey="Farmer L" first="Linda" last="Farmer">Linda Farmer</name>
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<name sortKey="Scollan, Nigel D" sort="Scollan, Nigel D" uniqKey="Scollan N" first="Nigel D" last="Scollan">Nigel D. Scollan</name>
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<country name="Australie"><noRegion><name sortKey="Polkinghorne, Rod" sort="Polkinghorne, Rod" uniqKey="Polkinghorne R" first="Rod" last="Polkinghorne">Rod Polkinghorne</name>
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<name sortKey="Pethick, David W" sort="Pethick, David W" uniqKey="Pethick D" first="David W" last="Pethick">David W. Pethick</name>
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<country name="Norvège"><noRegion><name sortKey="R Dbotten, Rune" sort="R Dbotten, Rune" uniqKey="R Dbotten R" first="Rune" last="R Dbotten">Rune R Dbotten</name>
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<country name="Irlande (pays)"><noRegion><name sortKey="Allen, Paul" sort="Allen, Paul" uniqKey="Allen P" first="Paul" last="Allen">Paul Allen</name>
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