Centre for Genetic Improvement of Livestock, Department of Animal and Poultry Science, University of Guelph, ON, Canada.
J Anim Breed Genet. 2012 Feb;129(1):11-9. doi: 10.1111/j.1439-0388.2011.00929.x. Epub 2011 Apr 20.
Test-day (TD) records of milk, fat-to-protein ratio (F:P) and somatic cell score (SCS) of first-lactation Canadian Holstein cows were analysed by a three-trait finite mixture random regression model, with the purpose of revealing hidden structures in the data owing to putative, sub-clinical mastitis. Different distributions of the data were allowed in 30 intervals of days in milk (DIM), covering the lactation from 5 to 305 days. Bayesian analysis with Gibbs sampling was used for model inferences. Estimated proportion of TD records originated from cows infected with mastitis was 0.66 in DIM from 5 to 15 and averaged 0.2 in the remaining part of lactation. Data from healthy and mastitic cows exhibited markedly different distributions, with respect to both average value and the variance, across all parts of lactation. Heterogeneity of distributions for infected cows was also apparent in different DIM intervals. Cows with mastitis were characterized by smaller milk yield (down to -5 kg) and larger F:P (up to 0.13) and SCS (up to 1.3) compared with healthy contemporaries. Differences in averages between healthy and infected cows for F:P were the most profound at the beginning of lactation, when a dairy cow suffers the strongest energy deficit and is therefore more prone to mammary infection. Residual variances for data from infected cows were substantially larger than for the other mixture components. Fat-to-protein ratio had a significant genetic component, with estimates of heritability that were larger or comparable with milk yield, and was not strongly correlated with milk and SCS on both genetic and environmental scales. Daily milk, F:P and SCS are easily available from milk-recording data for most breeding schemes in dairy cattle. Fat-to-protein ratio can potentially be a valuable addition to SCS and milk yield as an indicator trait for selection against mastitis.
对加拿大荷斯坦奶牛初产牛的产奶量、乳脂率-蛋白比（F:P）和体细胞评分（SCS）的测试日（TD）记录进行了三性状有限混合随机回归模型分析，目的是揭示由于潜在的亚临床乳腺炎导致数据中隐藏的结构。在涵盖泌乳期 5 至 305 天的 30 天泌乳天数（DIM）间隔内，允许数据有不同的分布。使用 Gibbs 抽样贝叶斯分析进行模型推断。在 DIM 5 至 15 天的哺乳期，感染乳腺炎的 TD 记录比例估计为 0.66，而在泌乳期的其余部分平均为 0.2。在整个泌乳期，健康牛和乳腺炎牛的数据在平均值和方差方面表现出明显不同的分布。感染牛的分布异质性在不同的 DIM 间隔内也很明显。与健康牛相比，乳腺炎牛的产奶量较小（低至-5kg），F:P 较大（高达 0.13），SCS 较高（高达 1.3）。在泌乳初期，健康牛和感染牛的 F:P 平均值差异最大，此时奶牛遭受的能量亏损最强，因此更容易受到乳房感染。感染牛的数据残差方差明显大于其他混合成分。F:P 具有显著的遗传成分，其遗传力估计值大于或与产奶量相当，并且在遗传和环境尺度上与牛奶和 SCS 相关性不强。对于大多数奶牛育种计划来说，从牛奶记录数据中可以很容易地获得每日牛奶、F:P 和 SCS。F:P 可以作为 SCS 和产奶量的一个有价值的附加指标，作为乳腺炎选择的指示性状。
