Pangmao Santi, Thomson Peter C, Khatkar Mehar S
Sydney School of Veterinary Science, Faculty of Science, The University of Sydney, Camden, NSW 2570, Australia.
Dairy Cattle Research and Development Center, Pak Chong, Nakhon Ratchasima 30130, Thailand.
Anim Biosci. 2022 Oct;35(10):1499-1511. doi: 10.5713/ab.21.0559. Epub 2022 May 2.
This study was aimed to estimate the genetic parameters, including genetic and phenotypic correlations, of milk yield, lactation curve traits and milk composition of Thai dairy cattle from three government research farms.
The data of 25,789 test-day milk yield and milk composition records of 1,468 cattle from lactation 1 to 3 of Holstein Friesian (HF) and crossbred HF dairy cattle calved between 1990 and 2015 from three government research farms in Thailand were analysed. 305-day milk yield was estimated by the Wood model and a test interval method. The Wood model was used for estimating cumulative 305-day milk yield, peak milk yield, days to peak milk yield and persistency. Genetic parameters were estimated using linear mixed models with herd, breed group, year and season of calving as fixed effects, and animals linked to a pedigree as random effects, together with a residual error. Univariate models were used to estimate variance components, heritability, estimated breeding values (EBVs) and repeatability of each trait, while pairwise bivariate models were used to estimate covariance components and correlations between traits in the same lactation and in the same trait across lactations.
The heritability of 305-day milk yield, peak milk yield and protein percentage have moderate to high estimates ranging from 0.19 to 0.45 while days to peak milk yield, persistency and fat percentage have low heritability ranging from 0.08 to 0.14 in lactation 1 cows. Further, heritability of most traits considered was higher in lactation 1 compared with lactations 2 and 3. For cows in lactation 1, high genetic correlations were found between 305-day milk yield and peak milk yield (0.86±0.07) and days to peak milk yield and persistency (0.99±0.02) while estimates of genetic correlations between the remaining traits were imprecise due to the high standard errors. The genetic correlations within the traits across lactation were high. There was no consistent trend of EBVs for most traits in the first lactation over the study period.
Both the Wood model and test interval method can be used for milk yield estimates in these herds. However, the Wood model has advantages over the test interval method as it can be fitted using fewer test-day records and the estimated model parameters can be used to derive estimates of other lactation curve parameters. Milk yield, peak milk yield and protein percentage can be improved by a selection and mating program while days to peak milk yield, persistency and fat percentage can be improved by including into a selection index.
本研究旨在估计来自泰国三个政府研究农场的泰国奶牛的产奶量、泌乳曲线性状和牛奶成分的遗传参数,包括遗传和表型相关性。
分析了1990年至2015年间在泰国三个政府研究农场出生的1468头荷斯坦弗里生(HF)奶牛及其杂交奶牛第1至3胎次的25789条测定日产奶量和牛奶成分记录。采用伍德模型和测试间隔法估计305天产奶量。伍德模型用于估计累计305天产奶量、产奶高峰量、达到产奶高峰的天数和泌乳持续力。使用线性混合模型估计遗传参数,将牛群、品种组、产犊年份和季节作为固定效应,将与系谱相关的动物作为随机效应,同时考虑残差误差。单变量模型用于估计各性状的方差分量、遗传力、估计育种值(EBV)和重复性,而双变量模型用于估计同一泌乳期内各性状之间以及不同泌乳期同一性状之间的协方差分量和相关性。
在第1胎次奶牛中,305天产奶量、产奶高峰量和蛋白质百分比的遗传力估计值为中等至高,范围从0.19至0.45,而达到产奶高峰的天数、泌乳持续力和脂肪百分比的遗传力较低,范围从0.08至0.14。此外,与第2和第3胎次相比,第1胎次中大多数所考虑性状的遗传力更高。对于第1胎次的奶牛,发现305天产奶量与产奶高峰量之间(0.86±0.07)以及达到产奶高峰的天数与泌乳持续力之间(0.99±0.02)存在高遗传相关性,而其余性状之间的遗传相关性估计由于标准误较高而不精确。不同泌乳期内各性状之间的遗传相关性较高。在研究期间,第1胎次中大多数性状的EBV没有一致的趋势。
伍德模型和测试间隔法均可用于这些牛群的产奶量估计。然而,伍德模型优于测试间隔法,因为它可以使用较少的测定日记录进行拟合,并且估计的模型参数可用于推导其他泌乳曲线参数的估计值。产奶量、产奶高峰量和蛋白质百分比可通过选择和配种计划得到改善,而达到产奶高峰的天数、泌乳持续力和脂肪百分比可通过纳入选择指数得到改善。