文章基本信息

标题：Various Statistical Approaches to Assess and Predict Carcass and Meat Quality Traits
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作者：Marie-Pierre Ellies-Oury ; Jean-François Hocquette ; Sghaier Chriki 等
期刊名称：Foods
电子版ISSN：2304-8158
出版年度：2020
卷号：9
期号：4
页码：525-539
DOI：10.3390/foods9040525
出版社：MDPI Publishing
摘要：The 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.
关键词：optimization; meat quality; trade-off; meat standards Australia; carcass; bovine optimization ; meat quality ; trade-off ; meat standards Australia ; carcass ; bovine