Hammami H, Vandenplas J, Vanrobays M-L, Rekik B, Bastin C, Gengler N
Animal Science Unit, Gembloux Agro-Bio Tech, University of Liege, 5030 Gembloux, Belgium; National Fund for Scientific Research, 1000 Brussels, Belgium.
Animal Science Unit, Gembloux Agro-Bio Tech, University of Liege, 5030 Gembloux, Belgium; National Fund for Scientific Research, 1000 Brussels, Belgium.
J Dairy Sci. 2015 Jul;98(7):4956-68. doi: 10.3168/jds.2014-9148. Epub 2015 May 7.
Genetic parameters that considered tolerance for heat stress were estimated for production, udder health, and milk composition traits. Data included 202,733 test-day records for milk, fat, and protein yields, fat and protein percentages, somatic cell score (SCS), 10 individual milk fatty acids (FA) predicted by mid-infrared spectrometry, and 7 FA groups. Data were from 34,468 first-lactation Holstein cows in 862 herds in the Walloon region of Belgium and were collected between 2007 and 2010. Test-day records were merged with daily temperature-humidity index (THI) values based on meteorological records from public weather stations. The maximum distance between each farm and its corresponding weather station was 21km. Linear reaction norm models were used to estimate the intercept and slope responses of 23 traits to increasing THI values. Most yield and FA traits had phenotypic and genetic declines as THI increased, whereas SCS, C18:0, C18:1 cis-9, and 4 FA groups (unsaturated FA, monounsaturated FA, polyunsaturated FA, and long-chain FA) increased with THI. Moreover, the latter traits had the largest slope-to-intercept genetic variance ratios, which indicate that they are more affected by heat stress at high THI levels. Estimates of genetic correlations within trait between cold and hot environments were generally high (>0.80). However, lower estimates (<=0.67) were found for SCS, fat yield, and C18:1 cis-9, indicating that animals with the highest genetic merit for those traits in cold environments do not necessarily have the highest genetic merit for the same traits in hot environments. Among all traits, C18:1 cis-9 was the most sensitive to heat stress. As this trait is known to reflect body reserve mobilization, using its variations under hot conditions could be a very affordable milk biomarker of heat stress for dairy cattle expressing the equilibrium between intake and mobilization under warm conditions.
针对生产、乳房健康和乳成分性状，估计了考虑热应激耐受性的遗传参数。数据包括202,733条测试日记录，涉及牛奶、脂肪和蛋白质产量、脂肪和蛋白质百分比、体细胞评分（SCS）、通过中红外光谱预测的10种个体乳脂肪酸（FA）以及7个FA组。数据来自比利时瓦隆地区862个牛群中的34,468头头胎荷斯坦奶牛，收集时间为2007年至2010年。测试日记录与基于公共气象站气象记录的每日温度湿度指数（THI）值合并。每个农场与其相应气象站之间的最大距离为21公里。使用线性反应规范模型来估计23个性状对THI值增加的截距和斜率反应。随着THI升高，大多数产量和FA性状的表型和遗传值下降，而SCS、C18:0、C18:1顺-9以及4个FA组（不饱和FA、单不饱和FA、多不饱和FA和长链FA）随THI增加。此外，后几个性状具有最大的斜率与截距遗传方差比，这表明它们在高THI水平下受热应激影响更大。寒冷和炎热环境下性状内的遗传相关性估计值通常较高（>0.80）。然而，SCS、脂肪产量和C18:1顺-9的估计值较低（<=0.67），这表明在寒冷环境中这些性状遗传价值最高的动物在炎热环境中不一定具有相同性状的最高遗传价值。在所有性状中，C18:1顺-9对热应激最敏感。由于已知该性状反映体储备动员情况，利用其在炎热条件下的变化可能是一种非常经济实惠的奶牛热应激乳生物标志物，可体现温暖条件下奶牛摄入与动员之间的平衡。
