Animal Production Systems group, Wageningen University, P.O. Box 338, 6700 AH Wageningen, the Netherlands; Adaptation Physiology group, Wageningen University, P.O. Box 338, 6700 AH Wageningen, the Netherlands.
Adaptation Physiology group, Wageningen University, P.O. Box 338, 6700 AH Wageningen, the Netherlands.
J Dairy Sci. 2021 Feb;104(2):1887-1899. doi: 10.3168/jds.2020-18719. Epub 2020 Dec 11.
Shortening or omitting the dry period to improve the energy balance in early lactation have the trade-offs of reduction in milk production and loss of opportunity for dry-cow therapy (DCT; i.e., intramammary antibiotic use at dry-off). Customized dry-period strategies (i.e., deciding upon DCT and dry-period length per cow) could mitigate negative effects of short or no dry periods on milk production and udder health and simultaneously retain benefits from improved energy balance and fertility. In this study, we evaluated 3 decision trees to customize dry-period strategies for individual cows. In the control tree (CT), all cows had a 60-d dry period, with DCT if somatic cell count (SCC) was >150,000 cells/mL before dry-off. In decision tree 1 (T1), parity 1 and parity >1 cows were assigned DCT if SCC was ≥150,000 cells/mL and SCC ≥50,000 cells/mL, respectively; whereas in decision tree 2 (T2), the threshold for DCT was SCC ≥200,000 cells/mL for all animals. In T1 and T2, cows with DCT were assigned a 60-d dry period, whereas cows without DCT were assigned a 30-d or 0-d dry period if their milk production remained >12 kg/d at 67 and 37 d before calving, respectively. Cows were monitored from 8 wk before to 14 wk after calving. Milk production and composition, SCC, body condition score, body weight, and occurrence of treatment for disease (related to calving and start of lactation) were compared between CT (n = 61 cows), T1 (n = 59 cows), and T2 (n = 63 cows). Effects of decision trees (CT, T1, T2) and of dry-period strategies (60-d dry with or without antibiotics, 30-d dry, or 0-d dry) on measured variables were analyzed separately with mixed models, effects on udder-health status with a logistic regression, and occurrence of treatment for diseases with a Pearson chi-squared test. In T1, 36% of cows qualified for 30-d and 2% for 0-d dry periods, whereas in T2 this was 51% and 30% for 30-d and 0-d dry periods, respectively. Compared with CT, cows in T1 and T2 on average produced more milk in the 8 wk before calving (0.2 vs. 3.9 vs. 7.1 kg/d in CT vs. T1 vs. T2), and less in the 14 wk after calving (40.0 vs. 37.0 vs. 35.2 kg/d in CT vs. T1 vs. T2). There was no difference in udder-health status in the transition period among decision trees. In the first 14 wk after calving, recovery of body weight was greater for T2 than CT and T1. Overall, 30-d and 0-d dry periods reduced milk revenues, but this might be financially compensated by improved cow health with customized dry-period strategies.
缩短或取消干奶期以改善泌乳早期的能量平衡，这会带来产奶量减少和错失干奶期治疗（即干奶时使用乳房内抗生素）机会的代价。定制干奶期策略（即根据每头牛决定干奶期治疗和干奶期长度）可以减轻短干奶期或无干奶期对产奶量和乳房健康的负面影响，同时保持能量平衡和繁殖力改善的益处。在这项研究中，我们评估了 3 种决策树来为个体奶牛定制干奶期策略。在对照树（CT）中，所有奶牛的干奶期为 60 天，如果在干奶前体细胞计数（SCC）>150,000 个/毫升，则进行干奶期治疗。在决策树 1（T1）中，初产和经产奶牛的 SCC 分别≥150,000 个/毫升和≥50,000 个/毫升时，给予干奶期治疗；而在决策树 2（T2）中，所有动物的干奶期治疗阈值为 SCC≥200,000 个/毫升。在 T1 和 T2 中，接受干奶期治疗的奶牛给予 60 天的干奶期，而未接受干奶期治疗的奶牛，如果在分娩前 67 和 37 天的产奶量仍>12 公斤/天，则给予 30 天或 0 天的干奶期。奶牛从分娩前 8 周到分娩后 14 周进行监测。比较了对照树（CT，n=61 头奶牛）、决策树 1（T1，n=59 头奶牛）和决策树 2（T2，n=63 头奶牛）之间的产奶量和组成、SCC、体况评分、体重以及与分娩和泌乳开始相关的疾病治疗情况。分别使用混合模型分析决策树（CT、T1、T2）和干奶期策略（60 天干奶期加或不加抗生素、30 天干奶期或 0 天干奶期）对测量变量的影响，使用逻辑回归分析对乳房健康状况的影响，使用皮尔逊卡方检验分析疾病治疗的发生情况。在 T1 中，36%的奶牛有资格进行 30 天干奶期，2%的奶牛有资格进行 0 天干奶期，而在 T2 中，分别有 51%和 30%的奶牛有资格进行 30 天和 0 天干奶期。与 CT 相比，T1 和 T2 的奶牛在分娩前 8 周的产奶量更高（CT 为 0.2 公斤/天，T1 为 3.9 公斤/天，T2 为 7.1 公斤/天），而在分娩后 14 周的产奶量更低（CT 为 40.0 公斤/天，T1 为 37.0 公斤/天，T2 为 35.2 公斤/天）。在决策树之间，过渡期间的乳房健康状况没有差异。在分娩后前 14 周，T2 比 CT 和 T1 恢复体重的速度更快。总的来说，30 天和 0 天干奶期减少了牛奶收入，但这可能会因定制干奶期策略提高奶牛健康水平而得到经济补偿。
