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

Abstract

The beef industry is organized around di erent stakeholders, each with their own expectations, sometimes antagonistic. This article first outlines these di ering 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. Di erent 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 di erent parameters of interest. Finally, some principles for the management of quality trade-o s are presented and the Meat Standards Australia model is discussed. The “Pareto front” is an interesting approach to deal jointly with the di erent sets of expectations and to propose a method that could optimize all expectations together

Description

Publication history: Accepted - 8 April 2020; Published - 22 April 2020.

Keywords

optimization, meat quality, trade-off, meat standards Australia, carcass, bovine

Citation

Ellies-Oury, M.-P., Hocquette, J.-F., Chriki, S., Conanec, A., Farmer, L., Chavent, M. and Saracco, J. (2020) ‘Various Statistical Approaches to Assess and Predict Carcass and Meat Quality Traits’, Foods. MDPI AG, 9(4), p. 525. doi: 10.3390/foods9040525.

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