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Evaluation of the accuracy of simple body measurements for live weight prediction in growing-finishing pigs

机译:评估生长肥育猪活体重预测的简单体测量的准确性

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摘要

Two studies were carried out to evaluate the accuracy of simple body measurements to predict the live weight of growing-finishing pigs. Study I used 72 barrows from a Landrace-based line; Study II used 72 barrows from each of a Landrace-based (the same line as used in Study I) and a Duroc-based line. Study I was carried out between 57.5 ?? 7.1 and 126.6 ?? 7.45 kg BW; Study II between 40.6 ?? 4.9 and 126 ?? 8.4 kg BW. In both studies, pigs were weighed every 2 wk and various body dimensions were taken on the live animal and on dorsal- and lateral-view photographic images of the pig taken at the time of weighing. Stepwise regression analysis was used to develop equations to predict live weight from body measurements. The highest R2 values were obtained for regression equations based on live animal measurements such as chest circumference [R2= 0.95; Residual Standard Deviation (RSD) = 5.7 kg], and flank circumference (R2= 0.94; RSD = 6.5 kg). Regression equations based on live-animal measurements generally gave higher R2 values than those based on measurements on the photographic images; e.g., in Study I the equation based on shoulder height gave R2 of 0.84 (RSD = 10.5 kg) for the measurement taken on the live animal compared to R2 of 0.26 (RSD = 18.2 kg) for the same measurement taken on the lateral image. Combining measurements to calculate body surface areas or volumes gave little improvement in R2 when those for the respective individual measurements were already high. Estimates of weighing period, and genotype biases for weight prediction were small, although, significant (P > 0.05) for the prediction equations from both studies. The results of this study suggest that regression equations based on simple body measurements can be used to accurately predict live weight of growing-finishing pigs.
机译:进行了两项研究,以评估简单的身体测量以预测生长肥育猪的活重的准确性。研究中,我使用了基于Landrace的品系中的72个手推车。研究II从基于Landrace的系(与研究I中使用的系相同)和基于Duroc的系中的每一个使用72个手推车。研究我是在57.5之间进行的。 7.1和126.6 ?? 7.45公斤体重;研究二之间40.6 ?? 4.9和126 ?? 8.4公斤体重。在这两项研究中,每2周对猪称重一次,对活体动物以及在称重时所拍摄的猪的背侧和侧向照相图像拍摄各种体型。使用逐步回归分析来开发方程式,以根据人体测量结果预测体重。基于诸如胸围等活体动物测量值的回归方程,获得了最高的R2值[R2 = 0.95;残余标准偏差(RSD)= 5.7 kg],齿腹周长(R2 = 0.94; RSD = 6.5 kg)。基于活体动物测量的回归方程通常比基于摄影图像测量的回归方程具有更高的R2值。例如,在研究I中,基于肩高的方程式对活体动物进行的测量得出R2为0.84(RSD = 10.5 kg),而对于侧面图像进行的相同测量得出的R2为0.26(RSD = 18.2 kg)。当用于各个单独测量的测量值已经很高时,将测量结果组合起来以计算人体表面积或体积不会对R2产生什么改善。尽管两项研究的预测方程均具有显着性(P> 0.05),但权重估计的估计期和基因型偏差很小。这项研究的结果表明,基于简单身体测量的回归方程可用于准确预测生长肥育猪的活体重。

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  • 作者

    Ochoa Zaragoza Luis Enrique;

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  • 年度 2010
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  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"English","id":9}
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