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

Author:

Siddell J.,McLeod B. M.,Toohey E. S.,van de Ven R.,Hopkins D. L.

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.

Publisher

CSIRO Publishing

Subject

Animal Science and Zoology,Food Science

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3