Department of Animal Bioscience, Animal and Grassland Research and Innovation Centre, Teagasc, Moorepark, Fermoy, Co. Cork, Ireland P61 C996; Department of Biological Sciences, Munster Technological University, Bishopstown Campus, Co. Cork, Ireland T12 P928.
Department of Biological Sciences, Munster Technological University, Bishopstown Campus, Co. Cork, Ireland T12 P928.
J Dairy Sci. 2022 Apr;105(4):3341-3354. doi: 10.3168/jds.2021-21306. Epub 2022 Feb 3.
The inclusion of reproductive performance in dairy cow breeding schemes has resulted in a cumulative improvement in genetic merit for reproductive performance; this improvement should manifest in longer productive lives through a reduced requirement for involuntary culling. Nonetheless, the average length of dairy cow productive life has not changed in most populations, suggesting that risk factors for culling, especially in older cows, are possibly more associated with lower yield or high somatic cell score (SCS) than compromised reproductive performance. The objective of the present study was to understand the dynamics of lactation yields and SCS in dairy cows across parities and, in doing so, quantify the potential to alter this trajectory through breeding. After edits, 3,470,520 305-d milk, fat, and protein yields, as well as milk fat and protein percentage and somatic cell count records from 1,162,473 dairy cows were available for analysis. Random regression animal models were used to identify the parity in which individual cows reached their maximum lactation yields, and highest average milk composition and SCS; also estimated from these models were the (co)variance components for yield, composition, and SCS per parity across parities. Estimated breeding values for all traits per parity were calculated for cows reaching ≥fifth parity. Of the cows included in the analyses, 91.0%, 92.2%, and 83.4% reached maximum milk, fat, and protein yield in fifth parity, respectively. Conversely, 95.9% of cows reached their highest average fat percentage in first parity and 62.9% of cows reached their highest average protein percentage in third parity. In contrast to both milk yield and composition traits, 98.4% of cows reached their highest average SCS in eighth parity. Individual parity estimates of heritability for milk yield traits, milk composition, and SCS ranged from 0.28 to 0.44, 0.47 to 0.69, and 0.13 to 0.23, respectively. The strength of the genetic correlations per trait among parities was inversely related to the interval between the parities compared; the weakest genetic correlation was 0.67 (standard error = 0.02) between milk yield in parities 1 and 8. Eigenvalues and eigenfunctions of the additive genetic covariance matrices for all investigated traits revealed potential to alter the trajectory of parity profiles for milk yield, milk composition, and SCS. This was further demonstrated when evaluating the trajectories of animal estimated breeding values per parity.
奶牛繁殖性能纳入选育方案，导致奶牛繁殖性能遗传进展得以累加；通过减少非意愿淘汰，这种改进应该会使奶牛生产寿命延长。然而，在大多数群体中，奶牛的平均生产寿命并未改变，这表明淘汰的风险因素，特别是在老年奶牛中，可能与较低的产奶量或较高的体细胞评分（SCS）有关，而不是与繁殖性能受损有关。本研究的目的是了解奶牛各胎次的泌乳量和 SCS 的动态变化，并在此基础上通过选育来量化改变这种变化轨迹的潜力。经过编辑，3470520 头 305 天牛奶、脂肪和蛋白质产量，以及 1162473 头奶牛的牛奶脂肪和蛋白质百分比和体细胞计数记录，可用于分析。随机回归动物模型用于确定个体奶牛达到其最大泌乳量和最高平均牛奶成分和 SCS 的胎次；还从这些模型中估计了各胎次的产量、成分和 SCS 的（协）方差分量。为达到第五胎次及以上的奶牛计算了各胎次的所有性状的估计育种值。在所分析的奶牛中，91.0%、92.2%和 83.4%的奶牛分别在第五胎次达到最大牛奶、脂肪和蛋白质产量。相反，95.9%的奶牛在第一胎次达到最高平均脂肪百分比，62.9%的奶牛在第三胎次达到最高平均蛋白质百分比。与牛奶产量和成分性状不同，98.4%的奶牛在第八胎次达到最高平均 SCS。牛奶产量性状、牛奶成分和 SCS 的个体胎次估计遗传力范围分别为 0.28 至 0.44、0.47 至 0.69 和 0.13 至 0.23。各性状各胎次之间遗传相关的强度与比较的胎次间隔呈反比；最弱的遗传相关为 0.67（标准误差=0.02），在第一胎和第八胎之间。所有研究性状的加性遗传协方差矩阵的特征值和特征函数表明，有可能改变牛奶产量、牛奶成分和 SCS 的胎次分布轨迹。当评估各胎次动物估计育种值的轨迹时，这一点得到了进一步证明。
