Department of Animal Science, São Paulo State University (FCAV/UNESP), Jaboticabal, SP, Brazil.
J Anim Breed Genet. 2010 Oct;127(5):369-76. doi: 10.1111/j.1439-0388.2010.00857.x.
The objective of this work was to estimate covariance functions for additive genetic and permanent environmental effects and, subsequently, to obtain genetic parameters for buffalo's test-day milk production using random regression models on Legendre polynomials (LPs). A total of 17 935 test-day milk yield (TDMY) from 1433 first lactations of Murrah buffaloes, calving from 1985 to 2005 and belonging to 12 herds located in São Paulo state, Brazil, were analysed. Contemporary groups (CGs) were defined by herd, year and month of milk test. Residual variances were modelled through variance functions, from second to fourth order and also by a step function with 1, 4, 6, 22 and 42 classes. The model of analyses included the fixed effect of CGs, number of milking, age of cow at calving as a covariable (linear and quadratic) and the mean trend of the population. As random effects were included the additive genetic and permanent environmental effects. The additive genetic and permanent environmental random effects were modelled by LP of days in milk from quadratic to seventh degree polynomial functions. The model with additive genetic and animal permanent environmental effects adjusted by quintic and sixth order LP, respectively, and residual variance modelled through a step function with six classes was the most adequate model to describe the covariance structure of the data. Heritability estimates decreased from 0.44 (first week) to 0.18 (fourth week). Unexpected negative genetic correlation estimates were obtained between TDMY records at first weeks with records from middle to the end of lactation, being the values varied from -0.07 (second with eighth week) to -0.34 (1st with 42nd week). TDMY heritability estimates were moderate in the course of the lactation, suggesting that this trait could be applied as selection criteria in milking buffaloes.
本研究旨在使用 Legendre 多项式（LP）的随机回归模型估计加性遗传和永久环境效应的协方差函数，并随后获得水牛产奶测试日（TDMY）的遗传参数。分析了来自巴西圣保罗州 12 个牛群的 1433 头首产泌乳水牛的 17935 个 TDMY，其产犊时间为 1985 年至 2005 年。当代群（CG）通过牛群、年份和泌乳测试月份定义。残差方差通过二阶至四阶方差函数以及具有 1、4、6、22 和 42 个类别的阶跃函数进行建模。分析模型包括 CG 的固定效应、挤奶次数、牛产犊时的年龄（线性和二次）以及群体的平均趋势。随机效应包括加性遗传和永久环境效应。加性遗传和永久环境随机效应通过乳天数的 LP 模型进行模拟，从二次到七次多项式函数。分别用五阶和六阶 LP 调整加性遗传和动物永久环境效应，以及用具有六个类别的阶跃函数模拟残差方差的模型，是描述数据协方差结构的最合适模型。遗传力估计值从第一周的 0.44 下降到第四周的 0.18。在泌乳早期与中期至后期之间，TDMY 记录之间获得了意外的负遗传相关估计值，其值从-0.07（第二周与第八周）到-0.34（第一周与第 42 周）不等。泌乳期间 TDMY 的遗传力估计值适中，表明该性状可作为奶用水牛的选择标准。
