title: Modelling of beef sensory quality for a better prediction of palatability.
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.).
authors.affiliation: INRA, UMRH 1213, Unité de Recherches sur les Herbivores, Theix, 63122 Saint Genès Champanelle, France; VetAgro Sup, UMRH 1213, Unité de Recherches sur les Herbivores, Theix, 63122 Saint Genès Champanelle, France. Electronic address: jfhocquette@clermont.inra.fr.
authors.forename: Jean-François
authors.initials: JF
authors.lastname: Hocquette
authors.affiliation: Ghent University, Department of Agricultural Economics, Coupure Links 653, B-9000 Ghent, Belgium.
authors.forename: Lynn
authors.initials: L
authors.lastname: Van Wezemael
authors.affiliation: INRA, UMRH 1213, Unité de Recherches sur les Herbivores, Theix, 63122 Saint Genès Champanelle, France; VetAgro Sup, UMRH 1213, Unité de Recherches sur les Herbivores, Theix, 63122 Saint Genès Champanelle, France; UNCEIA, 149 rue de Bercy, F-75595 Paris Cedex 12, France.
authors.forename: Sghaier
authors.initials: S
authors.lastname: Chriki
authors.affiliation: Institut de l'Elevage, Service Qualite' des Viandes, MRAL, 87060 Limoges Cedex 2, France.
authors.forename: Isabelle
authors.initials: I
authors.lastname: Legrand
authors.affiliation: Ghent University, Department of Agricultural Economics, Coupure Links 653, B-9000 Ghent, Belgium.
authors.forename: Wim
authors.initials: W
authors.lastname: Verbeke
authors.affiliation: Agri-Food and Biosciences Institute (AFBI), Food Science Branch, Newforge Lane, Belfast, Northern Ireland BT9 5PX, United Kingdom.
authors.forename: Linda
authors.initials: L
authors.lastname: Farmer
authors.affiliation: Institute of Biological Environmental and Rural Science, Aberystwyth University, Wales SY233EB, United Kingdom.
authors.forename: Nigel D
authors.initials: ND
authors.lastname: Scollan
authors.affiliation: 431 Timor Road, Murrurundi, NSW 2338, Australia.
authors.forename: Rod
authors.initials: R
authors.lastname: Polkinghorne
authors.affiliation: Nofima AS, Norwegian institute of Food, Fisheries and Aquaculture Research, P.O. Box 210, N-1431 Ås, Norway.
authors.forename: Rune
authors.initials: R
authors.lastname: Rødbotten
authors.affiliation: Teagasc Food Research Centre Ashtown, Dublin 15, Ireland.
authors.forename: Paul
authors.initials: P
authors.lastname: Allen
authors.affiliation: Murdoch University, Murdoch, WA 6150, Australia.
authors.forename: David W
authors.initials: DW
authors.lastname: Pethick
mesh_terms: D000818:Animals; D001315:Australia; D002417:Cattle; D005060:Europe; D006801:Humans; D008460:Meat / Q000032:analysis* / Q000592:standards; D008954:Models, Biological; D009132:Muscles; D011786:Quality Control; D013314:Stress, Mechanical; D013649:Taste
keywords: Beef; Eating quality; Modelling; Quality assurance scheme; Quality marks