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Various Statistical Approaches to Assess and Predict Carcass and Meat Quality Traits

hal.structure.identifierBordeaux Sciences Agro [Gradignan]
dc.contributor.authorELLIES-OURY, Marie-Pierre
hal.structure.identifierUnité Mixte de Recherche sur les Herbivores - UMR 1213 [UMRH]
dc.contributor.authorHOCQUETTE, Jean-François
hal.structure.identifierUnité Mixte de Recherche sur les Herbivores - UMR 1213 [UMRH]
dc.contributor.authorCHRIKI, Sghaier
hal.structure.identifierUnité Mixte de Recherche sur les Herbivores - UMR 1213 [UMRH]
dc.contributor.authorCONANEC, Alexandre
hal.structure.identifierAgri Food and Biosciences Institute
dc.contributor.authorFARMER, Linda
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
hal.structure.identifierQuality control and dynamic reliability [CQFD]
dc.contributor.authorCHAVENT, Marie
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
hal.structure.identifierQuality control and dynamic reliability [CQFD]
dc.contributor.authorSARACCO, Jérôme
dc.date.accessioned2024-04-04T02:54:52Z
dc.date.available2024-04-04T02:54:52Z
dc.date.issued2020
dc.identifier.issn2304-8158
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/192313
dc.description.abstractEnThe beef industry is organized around different stakeholders, each with their own expectations, sometimes antagonistic. This article first outlines these differing perspectives. Then, various optimization models that might integrate all these expectations are described. The final goal is to define practices that could increase value for animal production, carcasses and meat whilst simultaneously meeting the main expectations of the beef industry. Different models previously developed worldwide are proposed here. Two new computational methodologies that allow the simultaneous selection of the best regression models and the most interesting covariates to predict carcass and/or meat quality are developed. Then, a method of variable clustering is explained that is accurate in evaluating the interrelationships between different parameters of interest. Finally, some principles for the management of quality trade-offs are presented and the Meat Standards Australia model is discussed. The “Pareto front” is an interesting approach to deal jointly with the different sets of expectations and to propose a method that could optimize all expectations together.
dc.language.isoen
dc.publisherMDPI
dc.subject.enBovine
dc.subject.enCarcass
dc.subject.enMeat standards Australia
dc.subject.enTrrade-o
dc.subject.enMeat quality
dc.subject.enOptimization
dc.title.enVarious Statistical Approaches to Assess and Predict Carcass and Meat Quality Traits
dc.typeArticle de revue
dc.identifier.doi10.3390/foods9040525
dc.subject.halSciences du Vivant [q-bio]
bordeaux.journalFoods
bordeaux.page525
bordeaux.volume9
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.issue4
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-02570376
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02570376v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Foods&rft.date=2020&rft.volume=9&rft.issue=4&rft.spage=525&rft.epage=525&rft.eissn=2304-8158&rft.issn=2304-8158&rft.au=ELLIES-OURY,%20Marie-Pierre&HOCQUETTE,%20Jean-Fran%C3%A7ois&CHRIKI,%20Sghaier&CONANEC,%20Alexandre&FARMER,%20Linda&rft.genre=article


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