1. Has breed any effect on beef sensory quality?
- Author
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Ian Richardson, S. Failla, John L. Williams, María del Mar Campo, Per Ertbjerg, A. Conanec, M-P. Ellies-Oury, Begoña Panea, Marie Chavent, Jérôme Saracco, J. F. Hocquette, Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), Unité Mixte de Recherche sur les Herbivores - UMR 1213 (UMRH), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Quality control and dynamic reliability (CQFD), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), University of Zaragoza - Universidad de Zaragoza [Zaragoza], Bristol Veterinary School, University of Helsinki, Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia agraria (CREA), Agrifood Research and Technology Centre of Aragon, Av. Monta˜nana, 930, Zaragoza, Spain, Méthodes avancées d’apprentissage statistique et de contrôle (ASTRAL), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Naval Group, Davies Research Centre, University of Adelaide, Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti (DiANA), Università cattolica del Sacro Cuore [Piacenza e Cremona] (Unicatt), Bordeaux Sciences Agro [Gradignan], Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Helsingin yliopisto = Helsingfors universitet = University of Helsinki, and Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia agraria = Council for Agricultural Research and Economics (CREA)
- Subjects
Marchigiana ,[SDV]Life Sciences [q-bio] ,Sensory system ,Sensory analysis ,0404 agricultural biotechnology ,Animal science ,medicine ,Flavor ,Mixed effect models ,2. Zero hunger ,General Veterinary ,biology ,0402 animal and dairy science ,food and beverages ,Fixed effect models ,04 agricultural and veterinary sciences ,biology.organism_classification ,040401 food science ,040201 dairy & animal science ,Breed ,Tenderness ,Lipid content ,Animal Science and Zoology ,Analysis of variance ,medicine.symptom ,Beef - Abstract
International audience; A total of 436 young cattle from 15 cattle breeds were reared in as similar conditions as possible to evaluate the impact of breed on sensory quality of beef from longissimus muscle determined by sensory analysis. Two statistical methods for processing the sensory data were compared. The analysis of variance with or without the panelist effect gave similar conclusions indicating that the robustness of the results was not dependent on the method chosen. The 4 meat descriptors (tenderness, juiciness, beef flavor and off-flavor) placed breeds into 5 groups using an unsupervised classification (hierarchical ascending classification). Aberdeen Angus, Highland and Jersey, that have a high lipid content in the muscle studied, differed from the other breeds in that they had a higher beef flavour. The dual-purpose and rustic breeds, Simmental, Casina and Marchigiana, produced significantly less juicy and less tender meat than that from breeds selected for meat production. Overall, despite significant differences previously identified for animal, carcass, muscle and beef traits for the same animals, differences in sensory scores between most of the breeds were small, with only significant differences between the few breeds that had extreme sensory profiles (such as Simmental and Pirenaica).
- Published
- 2021