Various Statistical Approaches to Assess and Predict Carcass and Meat Quality Traits
Date
2020-04-22
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Publisher
MDPI
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.
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Article
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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.