The prediction of meat yield in lamb carcasses using primal cut weights, carcass measures and the Hennessy Grading Probe

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Contents Vol 52(7)

doi:10.1071/AN11260

Food, Fibre and Pharmaceuticals from Animals

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The prediction of meat yield in lamb carcasses using primal cut weights, carcass measures and the Hennessy Grading Probe

J. Siddell ^A ^B, B. M. McLeod ^B, E. S. Toohey ^C, R. van de Ven ^D and D. L. Hopkins ^E ^F

^A Sheep CRC, CJ Hawkins Homestead, University of New England, Armidale, NSW 2351, Australia.
^B NSW Department of Primary Industries, Centre for Perennial Grazing Systems, Glen Innes, NSW 2370, Australia.
^C NSW Department of Primary Industries, PO Box 865, Dubbo, NSW 2830, Australia.
^D NSW Department of Primary Industries, Orange Agricultural Institute, Forest Road, Orange, NSW 2800, Australia.
^E NSW Department of Primary Industries, Centre for Red Meat and Sheep Development, PO Box 129, Cowra, NSW 2794, Australia.
^F Corresponding author. Email: david.hopkins@dpi.nsw.gov.au

Animal Production Science 52(7) 584-590 http://dx.doi.org/10.1071/AN11260
Submitted: 27 October 2011 Accepted: 6 March 2012 Published: 10 April 2012





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Abstract

A wide selection of crossbred lambs (n = 268) of mixed sex (ewes and wethers) were slaughtered at a commercial abattoir. Tissue depth at the GR site (thickness of tissue over the 12th rib 110 mm from the midline) was measured in the chiller using a GR knife (GR) and fatscore (1–5) was assessed on each carcass by abattoir personnel. Each carcass was subsequently broken down to a range of trimmed cuts (subprimals) and the meat yield in kilograms determined as the sum of the weights of these cuts. The best model for the prediction of meat yield was based on the weight of the 4-rib, untrimmed forequarter, fatscore and GR, which had a mean-squared prediction error of 0.96, but a simpler model based on weight of the forequarter and GR only had a marginally higher mean-squared prediction error at 0.97. In both models as either forequarter weight, GR or fatscore increased the meat yield increased. The predominant industry model for predicting meat yield in Australia uses carcass weight and tissue depth at the GR site, but these predictors were less useful than models based on forequarter weight. There was no significant improvement for the prediction of meat yield from the use of muscle or fat depths measured with a Hennessy Grading Probe or directly on the carcass with a ruler when a subset of 97 carcasses was examined. In this case the final model was based on the weight of the forequarter and the weight of the hind leg (R² = 95%). It is feasible to collect the weight of the forequarter before subprimal cut preparation and if this can be achieved under commercial conditions, a method for predicting meat yield automatically during this procedure could be applied.

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