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Live animal predictions of carcass components and marble score in beef cattle: model development and evaluation

Published online by Cambridge University Press:  16 March 2020

M. J. McPhee
Affiliation:
NSW Department of Primary Industries, Livestock Industries Centre, University of New England, Trevenna Road, Armidale, New South Wales, 2351, Australia
B. J. Walmsley
Affiliation:
Animal Genetics and Breeding Unit, NSW Department of Primary Industries, University of New England, Armidale, New South Wales, 2351, Australia
H. C. Dougherty
Affiliation:
NSW Department of Primary Industries, Livestock Industries Centre, University of New England, Trevenna Road, Armidale, New South Wales, 2351, Australia Department of Animal Science, University of New England, Armidale, New South Wales, 2351, Australia
W. A. McKiernan
Affiliation:
NSW Department of Primary Industries, Livestock Industries Centre, University of New England, Trevenna Road, Armidale, New South Wales, 2351, Australia
V. H. Oddy
Affiliation:
NSW Department of Primary Industries, Livestock Industries Centre, University of New England, Trevenna Road, Armidale, New South Wales, 2351, Australia
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Abstract

Until recently, beef carcass payment grids were predominantly based on weight and fatness categories with some adjustment for age, defined as number of adult teeth, to determine the price received by Australian beef producers for slaughter cattle. With the introduction of the Meat Standards Australia (MSA) grading system, the beef industry has moved towards payments that account for intramuscular fat (IMF) content (marble score (MarbSc)) and MSA grades. The possibility of a payment system based on lean meat yield (LMY, %) has also been raised. The BeefSpecs suite of tools has been developed to assist producers to meet current market specifications, specifically P8-rump fat and hot standard carcass weight (HCW). A series of equations have now been developed to partition empty body fat and fat-free weight into carcass fat-free mass (FFM) and fat mass (FM) and then into flesh FFM (FleshFFM) and flesh FM (FleshFM) to predict carcass components from live cattle assessments. These components then predict denuded lean (kg) and finally LMY (%) that contribute to emerging market specifications. The equations, along with the MarbSc equation, are described and then evaluated using two independent datasets. The decomposition of evaluation datasets demonstrates that error in prediction of HCW (kg), bone weight (BoneWt, kg), FleshFFM (kg), FleshFM (kg), MarbSc and chemical IMF percentage (ChemIMF%) is shown to be largely random error (%) in evaluation dataset 1, though error for ChemIMF% was primarily slope bias (%) in evaluation dataset 1, and BoneWt had substantial mean bias (%) in evaluation dataset 2. High modelling efficiencies of 0.97 and 0.95 for predicting HCW for evaluation datasets 1 and 2, respectively, suggest a high level of accuracy and precision in the prediction of HCW. The new outputs of the model are then described as to their role in estimating MSA index scores. The modelling system to partition chemical components of the empty body into carcass components is not dependent on the base modelling system used to derive empty body FFM and FM. This can be considered a general process that could be used with any appropriate model of body composition.

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Research Article
Copyright
© The Animal Consortium 2020

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Footnotes

a

Deceased

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