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利用体尺测量预测荷斯坦小母牛的体重和鬐甲高度。

Predicting body weight and wither height in Holstein heifers using body measurements.

作者信息

Heinrichs A J, Rogers G W, Cooper J B

机构信息

Department of Dairy and Animal Science, Pennsylvania State University, University Park 16802.

出版信息

J Dairy Sci. 1992 Dec;75(12):3576-81. doi: 10.3168/jds.S0022-0302(92)78134-X.

Abstract

Relationships between body weight, wither height, and various other body traits, including heart girth, body length, and hip width, were studied using data from six experiments with 2625 observations. Body weight and wither height were regressed on the other body traits. Regressions of body weight including the linear, quadratic, and cubic effects of a single independent variable (heart girth, wither height, hip width or body length) indicated that each measurement would be useful in predicting body weight (R2 > .95); the regression of body weight on heart girth had the highest R2, followed by hip width. Similarly, regressions of wither height on heart girth, wither height, hip width, or body length, including linear, quadratic, and cubic effects, yielded R2 > .99. Regressions considering multiple traits as independent variables showed that the addition of a second body trait added little to the already high multiple correlations found with a single variable. In management situations for which body weight or wither height cannot be measured, various other traits can be used to estimate these body measurements accurately.

摘要

利用来自六个实验的2625个观测数据,研究了体重、鬐甲高度与其他各种身体特征之间的关系,这些身体特征包括胸围、体长和臀宽。将体重和鬐甲高度对其他身体特征进行回归分析。对体重进行的回归分析,包括单个自变量(胸围、鬐甲高度、臀宽或体长)的线性、二次和三次效应,结果表明,每种测量方法都有助于预测体重(R2>.95);体重对胸围的回归分析R2最高,其次是臀宽。同样,鬐甲高度对胸围、鬐甲高度、臀宽或体长的回归分析,包括线性、二次和三次效应,得到的R2>.99。将多个特征作为自变量的回归分析表明,增加第二个身体特征对已经由单个变量得出的高多重相关性影响不大。在无法测量体重或鬐甲高度的管理情况下,可以使用各种其他特征来准确估计这些身体测量值。

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