Department of AGROBIOCHEM and Terra Teaching and Research Centre, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium.
Department of Valorisation of Agricultural Products, Agricultural Product Technology Unit, Animal Nutrition and Sustainability Unit, Walloon Agricultural Research Centre, 5030 Gembloux, Belgium.
J Dairy Sci. 2017 Jul;100(7):5578-5591. doi: 10.3168/jds.2016-11954. Epub 2017 May 17.
Many countries have pledged to reduce greenhouse gases. In this context, the dairy sector is one of the identified sectors to adapt production circumstances to address socio-environmental constraints due to its large carbon footprint related to CH emission. This study aimed mainly to estimate (1) the genetic parameters of 2 milk mid-infrared-based CH proxies [predicted daily CH emission (PME, g/d), and log-transformed predicted CH intensity (LMI)] and (2) their genetic correlations with milk production traits [milk (MY), fat (FY), and protein (PY) yields] from first- and second-parity Holstein cows. A total of 336,126 and 231,400 mid-infrared CH phenotypes were collected from 56,957 and 34,992 first- and second-parity cows, respectively. The PME increased from the first to the second lactation (433 vs. 453 g/d) and the LMI decreased (2.93 vs. 2.86). We used 20 bivariate random regression test-day models to estimate the variance components. Moderate heritability values were observed for both CH traits, and those values decreased slightly from the first to the second lactation (0.25 ± 0.01 and 0.22 ± 0.01 for PME; 0.18 ± 0.01 and 0.17 ± 0.02 for LMI). Lactation phenotypic and genetic correlations were negative between PME and MY in both first and second lactations (-0.07 vs. -0.07 and -0.19 vs. -0.24, respectively). More close scrutiny revealed that relative increase of PME was lower with high MY levels even reverting to decrease, and therefore explaining the negative correlations, indicating that higher producing cows could be a mitigation option for CH emission. The PME phenotypic correlations were almost equal to 0 with FY and PY for both lactations. However, the genetic correlations between PME and FY were slightly positive (0.11 and 0.12), whereas with PY the correlations were slightly negative (-0.05 and -0.04). Both phenotypic and genetic correlations between LMI and MY or PY or FY were always relatively highly negative (from -0.21 to -0.88). As the genetic correlations between PME and LMI were strong (0.71 and 0.72 in first and second lactation), the selection of one trait would also strongly influence the other trait. However, in animal breeding context, PME, as a direct quantity CH proxy, would be preferred to LMI, which is a ratio trait of PME with a trait already in the index. The range of PME sire estimated breeding values were 22.1 and 29.41 kg per lactation in first and second parity, respectively. Further studies must be conducted to evaluate the effect of the introduction of PME in a selection index on the other traits already included in this index, such as, for instance, fertility or longevity.
许多国家都承诺减少温室气体排放。在这种情况下,由于其与 CH 排放相关的巨大碳足迹,乳制品行业是确定的需要适应生产环境以应对社会环境限制的行业之一。本研究旨在主要估计(1)基于牛奶中红外的 2 种 CH 预测指标[预测的每日 CH 排放量(PME,g/d)和对数变换的预测 CH 强度(LMI)]的遗传参数,以及(2)它们与产奶性状[牛奶(MY)、脂肪(FY)和蛋白质(PY)产量]的遗传相关性,这些性状来自第一和第二胎次荷斯坦奶牛。共收集了 56957 头和 34992 头第一和第二胎次奶牛的 336126 个和 231400 个牛奶中红外 CH 表型,PME 从第一泌乳期到第二泌乳期增加(433 比 453 g/d),LMI 降低(2.93 比 2.86)。我们使用 20 个双变量随机回归测试日模型来估计方差分量。两个 CH 性状都表现出适度的遗传力,并且从第一泌乳期到第二泌乳期略有下降(PME 为 0.25 ± 0.01 和 0.22 ± 0.01;LMI 为 0.18 ± 0.01 和 0.17 ± 0.02)。在第一和第二泌乳期中,PME 与 MY 的表型和遗传相关性均为负(-0.07 比-0.07 和-0.19 比-0.24)。更仔细的观察表明,即使 PME 水平升高,相对升高幅度也较低,甚至会出现下降,因此解释了负相关,表明高产奶牛可能是减少 CH 排放的一种选择。在两个泌乳期中,PME 与 FY 和 PY 的表型相关性几乎都等于 0。然而,PME 与 FY 的遗传相关性略为正(0.11 和 0.12),而与 PY 的遗传相关性略为负(-0.05 和-0.04)。LMI 与 MY 或 PY 或 FY 的表型和遗传相关性均为高度负相关(-0.21 到-0.88)。由于 PME 和 LMI 之间的遗传相关性很强(第一和第二泌乳期中分别为 0.71 和 0.72),因此选择一个性状也会强烈影响另一个性状。然而,在动物育种背景下,PME 作为直接数量 CH 预测指标,将优先于 LMI,后者是 PME 与已经在指数中的性状的比率性状。PME 种公牛估计育种值的范围分别为第一和第二胎次每胎 22.1 和 29.41 kg。必须进一步研究引入 PME 对已经包含在该指数中的其他性状(例如,生育力或寿命)的选择指数的影响。