...
首页> 外文期刊>Revista Brasileira de Zootecnia >Common factors method to predict the carcass composition tissue in kid goats
【24h】

Common factors method to predict the carcass composition tissue in kid goats

机译:预测小山羊the体组成组织的常见因素方法

获取原文

摘要

The objective of this work was to analyze the interrelations among weights and carcass measures of the longissimus lumborum muscle thickness and area, and of sternum tissue thickness, measured directly on carcass and by ultrasound scan. Measures were taken on live animals and after slaughter to develop models of multiple linear regression, to estimate the composition of shoulder blade, from selected variables in 89 kids of both genders and five breed groups, raised in feedlot system. The variables considered relevant and not redundant on the information they carry, for the common factor analysis, were used in the carcass composition estimate development models. The presuppositions of linear regression models relative to residues were evaluated, the estimated residues were subjected to analysis of variance and the means were compared by the Student t test. Based in these results, the group of 32 initial variables could be reduced to four variables: hot carcass weight, rump perimeter, leg length and tissue height at the fourth sternum bone. The analysis of common factors was shown as an effective technique to study the interrelations among the independent variables. The measures of carcass dimension, alone, did not add any information to hot carcass weight. The carcass muscle weight can be estimated with high precision from simple models, without the need for information related to gender and breed, and they could be built based on carcass weight, which makes it easy to be applied. The fat and bones estimate models were not as accurate.
机译:这项工作的目的是分析体重和car体测量值之间的相互关系,这些测量值是腰直肌的肌肉厚度和面积以及胸骨组织厚度的直接测量,并通过超声扫描测量。对活体动物和屠宰后采取了措施,以开发多元线性回归模型,以从育肥系统中饲养的89个性别和五个品种组的儿童中选择的变量中,估计肩blade骨的组成。对于common因子分析,在considered体组成估计发展模型中使用了被认为相关且对它们携带的信息没有多余的变量。评估相对于残基的线性回归模型的预设,对估计的残基进行方差分析,并通过Student t检验比较均值。根据这些结果,可以将这组32个初始变量减少为四个变量:hot体重量,臀围,腿长和第四胸骨的组织高度。公共因子分析被认为是研究自变量之间相互关系的有效技术。单独测量of体尺寸并不能增加hot体热重。 simple体肌肉重量可以通过简单的模型进行高精度估算,而无需性别和品种相关信息,并且可以基于car体重量进行构建,因此易于应用。脂肪和骨骼的估计模型并不准确。

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号