There is no clear method to measure biological efficiency in grazing beef cows. The objective of this study was to evaluate a nutrition model to estimate biological efficiency in mature cows. Data from dams (n = 160) and their 2nd and 3rd progeny were collected from 1953 through 1980. Individual feed intake was measured at 28-d intervals for lifetime of dams and during 240-d lactation for progeny. Body weight of progeny were measured at birth and weaning, and dams at parturition and weaning each production cycle. Milk yield of dams was measured at 14-d intervals by hand milking. Metabolizable energy required (MER) and predicted milk energy yield (MEY) of each cow was computed using the CVDS beef cow model for each parity. Biological efficiency was computed as the ratio of cow ME intake (MEI) to calf weaning weight (WW) based on observed (MEI/WW) and predicted (MER/WW) values. Pearson correlation coefficients were computed using corr.test function in R software. Average (SD) cow weight, calf weaning weight, cow MEI, and observed MEY were 507 (81) and 548 (88) kg, 287 (49) and 294 (44) kg, 9406 (2695) and 9721 (2686) Mcal, and 1009 (538) and 1051 (521) Mcal, for progeny 2 and 3, respectively. Cow MEI and MER (0.87 and 0.85), and observed and predicted MEY (0.51 and 0.51) were positively correlated for progeny 2 and 3, respectively. The CVDS model under predicted cow MEI [mean bias = 1685 (1718) and 1658 (1702) Mcal] and MEY [mean bias = 82 (465) and 129 (450) Mcal] for progeny 2 and 3, respectively. Observed and predicted progeny feed intake were not correlated. Observed and predicted biological efficiency were positively correlated (0.63 and 0.61) for progeny 2 and 3, respectively. In conclusion, nutrition models can reasonably predict biological efficiency, but further refinement of the relationship between calf feed intake and milk yield could improve prediction.

中文翻译：

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71 评估成熟奶牛生物效率的 CVDS 肉牛模型

没有明确的方法来测量放牧肉牛的生物效率。本研究的目的是评估一种营养模型，以估计成熟奶牛的生物效率。从 1953 年到 1980 年收集了来自大坝 (n = 160) 及其第 2 和第 3 个后代的数据。在大坝的生命周期中以 28 天为间隔测量个体采食量，并在后代的 240 天泌乳期间测量个体采食量。在出生和断奶时测量后代体重，在每个生产周期测量母猪的体重。通过手工挤奶每隔 14 天测量一次大坝的产奶量。使用每胎次的 CVDS 肉牛模型计算每头奶牛的代谢能量需求 (MER) 和预测的产奶量 (MEY)。根据观察到的 (MEI/WW) 和预测的 (MER/WW) 值，将生物效率计算为奶牛 ME 摄入量 (MEI) 与小牛断奶体重 (WW) 的比率。使用 R 软件中的 corr.test 函数计算 Pearson 相关系数。平均 (SD) 奶牛体重、犊牛断奶体重、奶牛 MEI 和观察到的 MEY 分别为 507 (81) 和 548 (88) kg、287 (49) 和 294 (44) kg、9406 (2695) 和 9721 (2686) Mcal , 和 1009 (538) 和 1051 (521) Mcal，分别用于后代 2 和 3。奶牛 MEI 和 MER（0.87 和 0.85）以及观察和预测的 MEY（0.51 和 0.51）分别与后代 2 和 3 呈正相关。预测奶牛 MEI [平均偏差 = 1685 (1718) 和 1658 (1702) Mcal] 和 MEY [平均偏差 = 82 (465) 和 129 (450) Mcal] 下的 CVDS 模型分别用于后代 2 和 3。观察到的和预测的后代采食量不相关。对于后代 2 和 3，观察到的和预测的生物学效率分别呈正相关（0.63 和 0.61）。总之，营养模型可以合理地预测生物效率，但进一步细化犊牛采食量和产奶量之间的关系可以改进预测。