Strategic Solutions Group, Puslinch, ON, Canada N0B 2J0.
J Dairy Sci. 2012 Mar;95(3):1358-62. doi: 10.3168/jds.2011-4927.
The objectives of this study were to quantify the relationship between 24-h milk loss and lactation milk loss due to mastitis at the cow level. For the year 2009, individual cow test-day production records from 2,835 Ontario dairy herds were examined. Each record consisted of 24-h milk and component yields, stage of lactation (days in milk, DIM), somatic cell count (SCC, ×10(3) cells/mL) and parity. The modeling was completed in 2 stages. In stage 1, for each animal in the study, the estimated slope from a linear regression of 24-h milk yield (kg), adjusted for DIM, the quadratic effect of DIM, and the 24-h fat yield (kg) on ln(SCC) was determined. In stage 2, the estimated slope were modeled using a mixed model with a random component due to herd. The fixed effects included season (warm: May to September, cool: October to April), milk quartile class [MQ, determined by the rank of the 24-h average milk yield (kg) over a lactation within the herd] and parity. The estimated slopes from the mixed model analysis were used to estimate 24-h milk loss (kg) by comparing to a referent healthy animal with an SCC value of 100 (×10(3) cells/mL) or less. Lactation milk loss (kg) was then estimated by using estimated 24-h milk loss within lactation by means of a test-day interval method. Lactation average milk loss (kg) and SCC were also estimated. Lastly, lactation milk loss (kg) was modeled on the log scale using a mixed model, which included the random effect of herd and fixed effects, parity, and the linear and quadratic effect of the number of 24-h test days within a lactation where SCC exceeded 100 (×10(3) cells/mL; S100). The effect of SCC was significant with respect to 24-h milk loss (kg), increasing across parity and MQ. In general, first-parity animals in the first MQ (lower milk yield animals) were estimated to have 45% less milk loss than later parity animals. Milk losses were estimated to be 33% less for animals in first parity and MQ 2 through 4 than later parity animals in comparable MQ. Therefore, the relative level of milk production was found to be a significant risk factor for milk loss due to mastitis. For animals with 24-h SCC, values of 200 (×10(3) cells/mL), 24-h milk loss ranged from 0.35 to 1.09 kg; with 24-h SCC values of 2,000 (×10(3) cells/mL), milk loss ranged from 1.49 to 4.70 kg. Lactation milk loss (kg) increased significantly as lactation average SCC increased, ranging from 165 to 919 kg. The linear and quadratic effect of S100 was a significant risk factor for lactation milk loss (kg), where greatest losses occurred in lactations with 5 or more 24-h test days where SCC exceeded 100 (×10(3) cells/mL).
本研究的目的是量化奶牛 24 小时产奶损失与乳腺炎引起的泌乳奶损失之间的关系。在 2009 年,检查了来自安大略省 2835 个奶牛场的 24 小时牛奶和成分产量、泌乳天数(DIM)、体细胞计数(SCC,每毫升 10,000 个细胞)和胎次的个体奶牛测试日生产记录。建模分为两个阶段进行。在第 1 阶段,对于研究中的每只动物,根据 DIM、DIM 的二次效应和 24 小时脂肪产量(kg),从 24 小时牛奶产量(kg)的线性回归中确定估计斜率ln(SCC)。在第 2 阶段,使用混合模型对估计斜率进行建模,该模型具有由于牧场造成的随机组件。固定效应包括季节(温暖:5 月至 9 月,凉爽:10 月至 4 月)、牛奶四分位数等级 [MQ,由牧场内泌乳期 24 小时平均牛奶产量(kg)的等级确定] 和胎次。使用混合模型分析得出的估计斜率来估计 24 小时牛奶损失(kg),方法是将 SCC 值为 100(每毫升 10,000 个细胞)或更低的健康动物进行比较。然后通过使用测试日间隔方法,根据在 SCC 超过 100(每毫升 10,000 个细胞)的泌乳期内估计的 24 小时牛奶损失,估计泌乳期牛奶损失(kg)。还估计了泌乳期平均牛奶损失(kg)和 SCC。最后,使用混合模型对数标度对泌乳期牛奶损失(kg)进行建模,该模型包括牧场的随机效应和固定效应、胎次以及 SCC 超过 100(每毫升 10,000 个细胞)的泌乳期内 24 小时测试天数的线性和二次效应;S100)。SCC 对 24 小时牛奶损失(kg)的影响是显著的,随着胎次和 MQ 的增加而增加。一般来说,第 1 胎次动物(产奶量较低的动物)的产奶损失估计比后期胎次动物少 45%。与可比 MQ 中的后期胎次动物相比,第 1 胎次和 MQ 2 至 4 的动物的牛奶损失估计减少了 33%。因此,相对产奶水平被发现是乳腺炎引起牛奶损失的一个重要风险因素。对于 24 小时 SCC 值为 200(每毫升 10,000 个细胞)的动物,24 小时牛奶损失范围为 0.35 至 1.09 公斤;对于 24 小时 SCC 值为 2,000(每毫升 10,000 个细胞)的动物,牛奶损失范围为 1.49 至 4.70 公斤。随着泌乳期平均 SCC 的增加,泌乳期牛奶损失(kg)显著增加,范围为 165 至 919 kg。S100 的线性和二次效应是泌乳期牛奶损失(kg)的重要风险因素,在 SCC 超过 100(每毫升 10,000 个细胞)的泌乳期内,5 次或更多 24 小时测试天数发生的损失最大。