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采用随机回归测定日模型对波兰黑白花奶牛头胎和二胎产奶量的遗传参数进行研究。

Genetic parameters for first and second lactation milk yields of Polish black and white cattle with random regression test-day models.

作者信息

Strabel T, Misztal I

机构信息

Department of Animal and Dairy Science, University of Georgia, Athens 30602, USA.

出版信息

J Dairy Sci. 1999 Dec;82(12):2805-10. doi: 10.3168/jds.S0022-0302(99)75538-4.

Abstract

Single- and two-trait random regression models were applied to estimate variance components of test-day records of milk, fat, and protein yields in the first and second lactation of Polish Black and White cattle. The model included fixed herd test-day effect, three covariates to describe lactation curve nested within age-season classes, and random regressions for additive genetic and permanent environmental effects. In two-parity models, each parity was treated as a separate trait. For milk and the two-parity model, heritabilities were in the range of 0.14 to 0.19 throughout first lactation and 0.10 to 0.16 throughout second lactation. For fat, heritabilities were within 0.11 to 0.16 and 0.11 to 0.22 throughout first and second lactations, respectively. For protein in the two-parity model, heritabilities were within 0.10 to 0.15 throughout most of first lactation and within 0.06 to 0.15 throughout the most of second lactation. For milk, genetic correlations between the first and second parities were 0.6 at the beginning of the lactation, rising to 0.9 in the middle, and 0.8 at the end of the lactation. For fat, the corresponding correlations were 0.6, 0.8, and 0.7, respectively, and for protein were 0.6, 0.8, and 0.8, respectively. Heritability estimates for all traits were flatter for the two-parity model. Relatively smooth genetic and permanent environmental variances with the two-parity model indicated that large swings of heritabilities could be artifacts of single-trait random regression models. High correlations between most of test day records across lactations suggested that a repeatability model could be considered as an alternative to a multiple-trait model to analyze multiple parities.

摘要

单性状和双性状随机回归模型被用于估计波兰黑白花奶牛头胎和二胎泌乳期奶、脂肪和蛋白质产量的测定日记录的方差分量。该模型包括固定的牛群测定日效应、用于描述年龄-季节类别内嵌套泌乳曲线的三个协变量,以及加性遗传效应和永久环境效应的随机回归。在双胎次模型中,每个胎次被视为一个单独的性状。对于奶产量和双胎次模型,头胎泌乳期的遗传力范围为0.14至0.19,二胎泌乳期为0.10至0.16。对于脂肪产量,头胎和二胎泌乳期的遗传力分别在0.11至0.16和0.11至0.22范围内。对于双胎次模型中的蛋白质产量,头胎泌乳期大部分时间的遗传力在0.10至0.15范围内,二胎泌乳期大部分时间在0.06至0.15范围内。对于奶产量,头胎和二胎泌乳期之间的遗传相关性在泌乳初期为0.6,中期升至0.9,泌乳末期为0.8。对于脂肪产量,相应的相关性分别为0.6、0.8和0.7,对于蛋白质产量分别为0.6、0.8和0.8。双胎次模型中所有性状的遗传力估计更为平缓。双胎次模型相对平滑的遗传和永久环境方差表明,遗传力的大幅波动可能是单性状随机回归模型的假象。不同泌乳期大多数测定日记录之间的高相关性表明,可考虑用重复性模型替代多性状模型来分析多个胎次。

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