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Dual energy X-ray absorptiometry precisely and accurately predicts lamb carcass composition at abattoir chain speed across a range of phenotypic and genotypic variables

Published online by Cambridge University Press:  13 May 2020

S. L. Connaughton Open the ORCID record for S. L. Connaughton [Opens in a new window] ,
A. Williams ,
F. Anderson ,
K. R. Kelman  and
G. E. Gardner
S. L. Connaughton*
Affiliation:
School of Veterinary and Life Sciences, Murdoch University, South Street, Murdoch6150, Western Australia, Australia
A. Williams
Affiliation:
School of Veterinary and Life Sciences, Murdoch University, South Street, Murdoch6150, Western Australia, Australia
F. Anderson
Affiliation:
School of Veterinary and Life Sciences, Murdoch University, South Street, Murdoch6150, Western Australia, Australia
K. R. Kelman
Affiliation:
School of Veterinary and Life Sciences, Murdoch University, South Street, Murdoch6150, Western Australia, Australia
G. E. Gardner
Affiliation:
School of Veterinary and Life Sciences, Murdoch University, South Street, Murdoch6150, Western Australia, Australia
*
†E-mail: [email protected]
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Abstract

Dual energy X-ray absorptiometry (DEXA) is an imaging modality that has been used to predict the computed tomography (CT)-determined carcass composition of multiple species, including sheep and pigs, with minimal inaccuracies, using medical grade DEXA scanners. An online DEXA scanner in an Australian abattoir has shown that a high level of precision can be achieved when predicting lamb carcass composition in real time. This study investigated the accuracy of that same online DEXA when predicting fat and lean percentages as determined by CT over a wide range of phenotypic and genotypic variables across 454 lambs over 6 kill groups and contrasted these results against the current Australian industry standard of grade-rule (GR) measurements to grade carcasses. Lamb carcasses were DEXA scanned and then CT scanned to determine CT Fat % and CT Lean %. All phenotypic traits and genotypic information, including Australian Sheep Breeding Values, were recorded for each carcass. Residuals of the DEXA predicted CT Fat % and Lean %, and the actual CT Fat % and Lean % were calculated and tested against all phenotypic and genotypic variables. Excellent overall precision was recorded when predicting CT Fat % (R2 = 0.91, RMSE = 1.19%). Small biases present for sire breed, sire type, dam breed, hot carcass weight and c-site eye muscle area could be explained by a regression paradox; however, biases among kill group (−0.73% to 1.01% for CT Fat %, −1.48% to 0.76% for CT Lean %) and the Merino sire type (0.36% for CT Fat %, −0.73% for CT Lean %) could not be explained by this effect. Over the large range of phenotypic and genotypic variation, there was excellent precision when predicting CT Fat % and CT Lean % by an online DEXA, with only minor biases, showing superiority to the existing Australian standard of GR measurements.

Keywords

sheepobjective measurementbiaslean meat yieldcomputed tomography
Type
Research Article
Information
animal , Volume 14 , Issue 10 , October 2020 , pp. 2194 - 2202
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of The Animal Consortium

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