Department of Animal and Food Sciences, Texas Tech University, Lubbock, TX 79409-2141, USA.
J Anim Sci. 2010 Sep;88(9):3009-17. doi: 10.2527/jas.2009-2626. Epub 2010 May 7.
Intake prediction equations were developed from a commercial feedlot database consisting of 3,363 pen means collected from 3 feedlots over a 4-yr period. The objective was to predict feeding-period average DMI from variables known at the start of the feeding period, including initial BW, sex, and average DMI from d 8 to 28 of the feeding period. Equations were evaluated within the same database using bootstrapping and cross-validation techniques. Bootstrapping evaluations of equations that included initial BW and sex explained approximately 57.0 to 73.2% of the variation in observed DMI with 90.5 to 96.6% accuracy, but DMI was overpredicted by 0.21 kg/d. Accuracy and precision improved with addition to the models of average DMI from d 8 to 28 of the feeding period; these models accounted for 68.0 to 83.0% of variation in observed DMI with model accuracy between 95.2 and 99.5% and overprediction of DMI by 0.05 kg/d. Cross-validation of developed equations confirmed the robust nature of chosen variables and the decrease in prediction error as sex and average DMI from d 8 to 28 were added to models based on initial shrunk BW (SBW). Bootstrapping and cross-validation evaluations were also conducted on the NRC (1996) NE(m)-based intake prediction equations with and without the NRC-recommended 4% decrease in predicted DMI and a 12% increase in dietary NE(m) concentration associated with the feeding of monensin. The average metabolic SBW used in these equations was computed from initial SBW and a predicted final SBW developed from the pen database. When these evaluations were performed, model precision decreased compared with simpler equations that included initial BW and sex, but using both adjustments for use of monensin improved the accuracy of the NRC equation. Nonetheless, the systematic bias proportion of the mean square error of prediction for bootstrapping analyses increased from 4.6 to 11.1% in the model with no adjustments to 16.3 to 38.9% in the model with both monensin adjustments, demonstrating these adjustments are less than optimal. Overall, variables that are typically available to feedlot managers when cattle are started on feed (e.g., initial BW, sex, and an early indication of DMI) were important predictors of feeding-period average DMI by pens of cattle.
从一个由 3363 个栏位平均值组成的商业养殖场数据库中开发了进料预测方程,这些数据是在 4 年期间从 3 个养殖场收集的。其目的是从进料期开始时已知的变量中预测进料期的平均每日采食量,包括初始体重、性别和进料期第 8 至 28 天的平均每日采食量。使用自举和交叉验证技术在同一数据库中评估了这些方程。包含初始体重和性别的方程的自举评估解释了观察到的采食量变化的 57.0%至 73.2%,准确率为 90.5%至 96.6%,但每日采食量的预测值偏高 0.21kg。随着对进料期第 8 至 28 天的平均每日采食量模型的加入,模型的准确性和精度得到了提高;这些模型解释了观察到的采食量变化的 68.0%至 83.0%,模型准确率在 95.2%至 99.5%之间,每日采食量的预测值偏高 0.05kg。对所开发方程的交叉验证证实了所选变量的稳健性以及随着基于初始收缩体重 (SBW) 的模型中添加性别和进料期第 8 至 28 天的平均每日采食量,预测误差的减少。还对 NRC(1996 年)基于 NE(m)的摄入量预测方程进行了自举和交叉验证评估,其中包括 NRC 推荐的预测每日采食量降低 4%和与使用莫能菌素相关的日粮 NE(m)浓度增加 12%。这些方程中使用的平均代谢性 SBW是由初始 SBW 和从栏位数据库中开发的预测终末 SBW 计算得出的。当进行这些评估时,与包含初始体重和性别等更简单的方程相比,模型的精度降低,但使用莫能菌素的两种调整都提高了 NRC 方程的准确性。尽管如此,在没有任何调整的模型中,预测误差的均方根误差的系统偏差比例从自举分析的 4.6%增加到 11.1%,在包含两种莫能菌素调整的模型中增加到 16.3%至 38.9%,表明这些调整并不理想。总体而言,当牛开始进食时,通常可供养殖场经理使用的变量(例如初始体重、性别和早期采食量的迹象)是牛栏平均每日采食量的重要预测指标。