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从整个育肥期应用的饲养管理系统特征因素预测牛胴体和肉质特性。

Prediction of beef carcass and meat quality traits from factors characterising the rearing management system applied during the whole life of heifers.

机构信息

Université Clermont Auvergne, INRA, VetAgro Sup, UMR Herbivores, F-63122 Saint-Genès-Champanelle, France.

Université de Clermont Auvergne, Université Blaise Pascal, Laboratoire de Mathématiques, BP 10448, F-63000 Clermont-Ferrand, France; CNRS, UMR 6620, Laboratoire de Mathématiques, F-63171 Aubière, France.

出版信息

Meat Sci. 2018 Jun;140:88-100. doi: 10.1016/j.meatsci.2018.03.009. Epub 2018 Mar 10.

DOI:10.1016/j.meatsci.2018.03.009
PMID:29549845
Abstract

In this study, four prediction models were developed by logistic regression using individual data from 96 heifers. Carcass and sensory rectus abdominis quality clusters were identified then predicted using the rearing factors data. The obtained models from rearing factors applied during the fattening period were compared to those characterising the heifers' whole life. The highest prediction power of carcass and meat quality clusters were obtained from the models considering the whole life, with success rates of 62.8% and 54.9%, respectively. Rearing factors applied during both pre-weaning and fattening periods influenced carcass and meat quality. According to models, carcass traits were improved when heifer's mother was older for first calving, calves ingested concentrates during pasture preceding weaning and heifers were slaughtered older. Meat traits were improved by the genetic of heifers' parents (i.e., calving ease and early muscularity) and when heifers were slaughtered older. A management of carcass and meat quality traits is possible at different periods of the heifers' life.

摘要

本研究通过使用 96 头小母牛的个体数据,利用逻辑回归建立了四个预测模型。鉴定了胴体和感官腹直肌质量聚类,然后使用饲养因素数据对其进行预测。比较了育肥期应用的饲养因素获得的模型与描述小母牛整个生命的模型。考虑整个生命的模型对胴体和肉质聚类的预测能力最高,成功率分别为 62.8%和 54.9%。在断奶前和育肥期应用的饲养因素影响胴体和肉质。根据模型,当小母牛的第一胎龄较大时,小牛在断奶前的牧场上摄入浓缩物,以及小母牛较老时,胴体特征得到改善。通过小母牛父母的遗传(即分娩容易和早期肌肉发达)和当小母牛较老时,肉的特性得到改善。可以在小母牛生命的不同时期对胴体和肉质特性进行管理。

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