1Department of Agronomy,Food,Natural Resources,Animals and Environment (DAFNAE),University of Padova,Viale dell'Università 16,35020 Legnaro (PD),Italy.
2Animal and Grassland Research and Innovation Center,Teagasc,Moorepark,Fermoy,Co. Cork P61 P302,Ireland.
Animal. 2019 Mar;13(3):477-486. doi: 10.1017/S1751731118001507. Epub 2018 Jul 6.
Milk mineral concentration is important from both the perspective of processing milk into dairy products and its nutritive value for human consumption. Precise estimates of genetic parameters for milk mineral concentration are lacking because of the considerable resources required to collect vast phenotypes quantities. The milk concentration of calcium (Ca), potassium (K), magnesium (Mg), sodium (Na) and phosphorus (P) in the present study was quantified from mid-IR spectroscopy on 12 223 test-day records from 1717 Holstein-Friesian cows. (Co)variance components were estimated using random regressions to model both the additive genetic and within-lactation permanent environmental variances of each trait. The coefficient of genetic variation averaged across days-in-milk (DIM) was 6.93%, 3.46%, 6.55%, 5.20% and 6.68% for Ca, K, Mg, Na and P concentration, respectively; heritability estimates varied across lactation from 0.31±0.05 (5 DIM) to 0.67±0.04 (181 DIM) for Ca, from 0.18±0.03 (60 DIM) to 0.24±0.05 (305 DIM) for K, from 0.08±0.03 (15 DIM) to 0.37±0.03 (223 DIM) for Mg, from 0.16±0.03 (30 DIM) to 0.37±0.04 (305 DIM) for Na and from 0.21±0.04 (12 DIM) to 0.57±0.04 (211 DIM) for P. Genetic correlations within the same trait across different DIM were almost unity between adjacent DIM but weakened as the time interval between pairwise compared DIM lengthened; genetic correlations were weaker than 0.80 only when comparing both peripheries of the lactation. The analysis of the geometry of the additive genetic covariance matrix revealed that almost 90% of the additive genetic variation was accounted by the intercept term of the covariance functions for each trait. Milk protein concentration and mineral concentration were, in general, positively genetically correlated with each other across DIM, whereas milk fat concentration was positively genetically correlated throughout the entire lactation with Ca, K and Mg; the genetic correlation with fat concentration changed from negative to positive with Na and P at 243 DIM and 50 DIM, respectively. Genetic correlations between somatic cell score and Na ranged from 0.38±0.21 (5 DIM) to 0.79±0.18 (305 DIM). Exploitable genetic variation existed for all milk minerals, although many national breeding objectives are probably contributing to an indirect positive response to selection in milk mineral concentration.
从加工牛奶制成乳制品的角度和其对人类消费的营养价值来看，牛奶矿物质浓度都很重要。由于收集大量表型数量需要大量资源，因此缺乏对牛奶矿物质浓度遗传参数的精确估计。本研究通过对 1717 头荷斯坦-弗里森奶牛的 12223 个测试日记录的中红外光谱，定量测定了牛奶中钙（Ca）、钾（K）、镁（Mg）、钠（Na）和磷（P）的浓度。使用随机回归模型估计协方差分量，以分别对每个性状的加性遗传和泌乳内永久性环境方差进行建模。在泌乳天数（DIM）内的遗传变异系数平均值分别为 Ca、K、Mg、Na 和 P 浓度的 6.93%、3.46%、6.55%、5.20%和 6.68%；Ca 的遗传力估计值从泌乳 5 DIM 时的 0.31±0.05 到泌乳 181 DIM 时的 0.67±0.04 不等，K 的遗传力估计值从泌乳 60 DIM 时的 0.18±0.03 到泌乳 305 DIM 时的 0.24±0.05 不等，Mg 的遗传力估计值从泌乳 15 DIM 时的 0.08±0.03 到泌乳 223 DIM 时的 0.37±0.03 不等，Na 的遗传力估计值从泌乳 30 DIM 时的 0.16±0.03 到泌乳 305 DIM 时的 0.37±0.04 不等，P 的遗传力估计值从泌乳 12 DIM 时的 0.21±0.04 到泌乳 211 DIM 时的 0.57±0.04 不等。同一性状在不同 DIM 内的遗传相关性在相邻 DIM 之间几乎为 1，但随着比较 DIM 之间的时间间隔延长而减弱；只有在比较泌乳的两个外围时，遗传相关性才弱于 0.80。加性遗传协方差矩阵的几何分析表明，几乎 90%的加性遗传变异由每个性状协方差函数的截距项解释。在 DIM 内，牛奶蛋白浓度和矿物质浓度通常与彼此呈正相关，而牛奶脂肪浓度在整个泌乳期与 Ca、K 和 Mg 呈正相关；与脂肪浓度的遗传相关性在与 Na 和 P 比较时，分别从负相关变为正相关，在 243 DIM 和 50 DIM 时。体细胞评分与 Na 之间的遗传相关性在 0.38±0.21（5 DIM）到 0.79±0.18（305 DIM）之间。所有牛奶矿物质都存在可利用的遗传变异，尽管许多国家的育种目标可能会对牛奶矿物质浓度的选择产生间接的正向反应。
