Nutrition models are important tools in management decisions, but improvements are needed for cow–calf producers to accurately predict nursing calf performance. Therefore, the objective of this study was to assess the ability of published milk yield (MY) and forage intake equations to predict calf feed intake and weaning weight (WW) using an independent, multi-breed dataset. A dataset with 406 nursing calves was used to evaluate two MY equations: 1) National Academies of Sciences, Engineering, and Medicine (2016) (NASEM) and 2) Wood (1967) (WOOD) and five feed intake equations: 1) equations from Table 9.1 in Tedeschi et al. (2006) (TED06), 2) equations 2 to 7 in Baker et al. (1976) (BAK76), 3) equation 25 in Tedeschi and Fox (2009) (TED09A), 4) equations 17, 19, and 24 in Tedeschi and Fox (2009) (TED09B), and 5) equation from Holloway et al. (1982) (HOL82). MY was measured at 14-d interval by hand milking, and individual feed intake of nursing calves was determined during a 240-d nursing period. Calf birth and WW were measured on days 0 and 240, respectively. Each combination of MY and feed intake equation was used to predict calf feed intake and WW from observed MY, calf birth weight, and calf slaughter weight. Predicted and observed values were compared using concordance correlation coefficient (CCC) and mean bias (MB). Factors affecting the deviation between observed and predicted values were analyzed using regression, and a revised equation was developed. Feed intake equations poorly predicted observed feed intake with CCC < 0.4 and MB ranged from −108% to 69%. However, statistics were slightly improved when using WOOD rather than the NASEM MY equation. BAK76 and TED09B feed intake equations were considerably more accurate (MB = −14.4% to 13.0%) in predicting feed intake but still not precise (CCC < 0.30). Predictions of WW had CCC ranging from 0.19 to 0.71 and MB ranging from −25.9% to 41.8% and were not significantly affected by the MY equation. TED06 and BAK76 feed intake equations were the most precise (CCC > 0.60) and accurate (MB = 1.7% to 8.5%) in predicting WW. Sire breed accounted for significant variation in the deviation between observed and predicted values of feed intake and in a revised equation to predict total feed energy intake from total milk energy intake. In conclusion, refinements of feed intake equations for nursing calves need to account for breed to improve current nutrition models.

中文翻译：

---

产奶量评估和犊牛采食量方程在预测品种间犊牛采食量和断奶体重中的作用

营养模型是管理决策的重要工具，但奶牛和小牛生产者需要改进以准确预测哺乳小牛的表现。因此，本研究的目的是使用独立的多品种数据集评估已公布的产奶量 ( MY ) 和饲草摄入量方程预测犊牛采食量和断奶体重 ( WW ) 的能力。使用包含 406 头护理犊牛的数据集来评估两个 MY 方程：1) 美国国家科学院、工程和医学院 (2016) ( NASEM ) 和 2) Wood (1967) ( WOOD ) 和五个采食量方程：1) 方程来自 Tedeschi 等人的表 9.1。(2006) ( TED06 ), 2) Baker 等人的方程 2 到 7。(1976) ( BAK76）; 3）式（25）中特德斯奇和福克斯（2009）（TED09A），4）方程17，19，和在特德斯奇和Fox（2009）（24 TED09B），和5）从霍洛维等方程。(1982) ( HOL82 )。通过手工挤奶每隔 14 天测量 MY，并在 240 天的护理期间确定护理犊牛的个体采食量。分别在第 0 天和第 240 天测量小牛出生和 WW。MY 和采食量方程的每种组合都用于根据观察到的 MY、犊牛出生体重和犊牛屠宰体重预测犊牛采食量和 WW。使用一致性相关系数 ( CCC ) 和平均偏差 ( MB）。使用回归分析了影响观察值和预测值之间偏差的因素，并制定了修正方程。CCC < 0.4 和 MB 范围从 -108% 到 69% 时，采食量方程无法预测观察到的采食量。然而，当使用 WOOD 而不是 NASEM MY 方程时，统计数据略有改进。BAK76 和 TED09B 采食量方程在预测采食量方面更加准确（MB = -14.4% 至 13.0%），但仍然不准确（CCC < 0.30）。WW 的预测具有 CCC 范围从 0.19 到 0.71 和 MB 范围从 -25.9% 到 41.8% 并且不受 MY 方程的显着影响。TED06 和 BAK76 的采食量方程在预测 WW 方面是最精确的（CCC > 0.60）和准确的（MB = 1.7% 到 8.5%）。公畜品种解释了饲料摄入量观察值和预测值之间偏差的显着变化，以及根据总牛奶能量摄入量预测总饲料能量摄入量的修正方程。总之，哺乳犊的采食量方程的改进需要考虑品种以改进当前的营养模型。