Excessive negative energy balance (EB) has been associated with decreased reproductive performance and increased risk of lameness and metabolic diseases. On-farm, automated EB estimates for individual cows would enable dairy farmers to detect excessive negative EB early and act to minimize its extent and duration by altering feeding. Previously, we have shown that EB can be estimated from frequent measurements of body weight (BW) and body condition score (BCS) changes, referred to as EB_body. In this study, we investigated the robustness and sensitivity of the EB_body method to assess its genericity and on-farm applicability. We used 5 data sets with BW of lactating cows (name of data set in parenthesis): 65 Holstein cows in a French feeding trial (INRA); 6 Holstein cows in a British feeding trial (Friggens); 31 Holstein cows and 17 Jersey cows in a Danish feeding trial (DCRC); 140 Holstein cows in a British feeding trial (Scotland's Rural College, SRUC); and 1,592 Holstein cows on 9 Danish farms with milking robots (automatic milking system). We used the INRA and Friggens data sets to develop a dynamic formula to correct BW for increasing residual gut-fill (RGF) during early lactation. With the DCRC data, we tested the effect of smoothing parameters and weighing frequency on EB_body. Also, 2 robustness tests were performed using the SRUC data to test the effect of diet change on BW and the automatic milking system data to test the effect of farm on BW variation. Finally, we combined the results into a blueprint describing different ways to calculate EB_body depending on the purpose and on the availability of BCS. The dynamic RGF adjustment resulted in a lower empty BW during early lactation than that obtained with the previously used constant RGF. The double-exponential smoothing method used to correct for meal-related gut-fill was robust to choice of smoothing parameters. Cows should be weighed at least once every 4 d during early lactation to capture the duration of negative EB_body. Our EB_body method proved robust to diet changes. Finally, although cow BW varied significantly between farms, the quantile regression smoothing of BW did not bias the estimation of weight differences between herds. In conclusion, these results validate the applicability of the EB_body method to estimate EB across a range of farm conditions, and we provided a blueprint that enables the estimation of EB_body for individual cows on-farm using only frequent BW, in combination with BCS when available.

过度的负能量平衡（EB）与生殖能力下降，la行和代谢疾病的风险增加有关。在农场上，对单个母牛的自动EB估计值将使奶牛养殖者能够及早发现过量的EB阴性，并通过改变饲喂来最大程度地减少其范围和持续时间。以前，我们已经表明，可以通过频繁测量体重（BW）和身体状况评分（BCS）变化（称为EB_体）来估计EB 。在这项研究中，我们调查了EB_机体的鲁棒性和敏感性评估其通用性和农场适用性的方法。我们使用了5个奶牛体重的数据集（括号内的数据集名称）：法国喂养试验（INRA）中的65头荷斯坦奶牛；在英国饲养试验中有6头荷斯坦奶牛（Friggens）；丹麦饲养试验（DCRC）中的31头荷斯坦奶牛和17头泽西奶牛；在英国的饲养试验中有140头荷斯坦奶牛（苏格兰农村学院，SRUC）；和9座丹麦农场的1,592头荷斯坦奶牛，配备了挤奶机器人（自动挤奶系统）。我们使用INRA和Friggens数据集来开发动态公式，以纠正体重偏高，以增加泌乳早期残留的肠填充物（RGF）。利用DCRC数据，我们测试了平滑参数和称重频率对EB_{车身的影响}。此外，还使用SRUC数据进行了2次鲁棒性测试，以测试饮食变化对体重的影响，并使用自动挤奶系统数据来测试农场对体重变化的影响。最后，我们将结果组合成一个蓝图，该蓝图描述了根据目的和BCS的可用性来计算EB_主体的不同方法。动态RGF调节导致早期哺乳期间的空腹体重低于以前使用的恒定RGF所获得的空腹体重。用于校正与餐有关的肠填充物的双指数平滑方法对于选择平滑参数具有鲁棒性。哺乳初期至少每4天称重一次母牛，以记录负EB_体的持续时间。我们的EB_机构事实证明该方法对饮食变化具有抵抗力。最后，尽管奶牛的体重在不同农场之间存在显着差异，但体重的分位数回归平滑处理并没有使牛群之间体重差异的估计产生偏差。总之，这些结果验证了EB_体方法在各种农场条件下估算EB的适用性，并且我们提供了一个蓝图，该蓝图使得仅使用频繁的BW结合BCS就可以对单个奶牛场的EB_体进行估算。有空的时候。