Animal Genetics and Breeding Division, ICAR-National Dairy Research Institute, Karnal, Haryana, India.
ICAR-National Bureau of Animal Genetic Resources, Karnal, India.
J Anim Breed Genet. 2024 Jul;141(4):365-378. doi: 10.1111/jbg.12849. Epub 2024 Jan 12.
The current study sought to genetically assess the lactation curve of Alpine × Beetal crossbred goats through the application of random regression models (RRM). The objective was to estimate genetic parameters of the first lactation test-day milk yield (TDMY) for devising a practical breeding strategy within the nucleus breeding programme. In order to model variations in lactation curves, 25,998 TDMY records were used in this study. For the purpose of estimating genetic parameters, orthogonal Legendre polynomials (LEG) and B-splines (BS) were examined in order to generate suitable and parsimonious models. A single-trait RRM technique was used for the analysis. The average first lactation TDMY was 1.22 ± 0.03 kg and peak yield (1.35 ± 0.02 kg) was achieved around the 7th test day (TD). The present investigation has demonstrated the superiority of the B-spline model for the genetic evaluation of Alpine × Beetal dairy goats. The optimal random regression model was identified as a quadratic B-spline function, characterized by six knots to represent the central trend. This model effectively captured the patterns of additive genetic influences, animal-specific permanent environmental effects (c) and 22 distinct classes of (heterogeneous) residual variance. Additive variances and heritability (h) estimates were lower in the early lactation, however, moderate across most parts of the lactation studied, ranging from 0.09 ± 0.04 to 0.33 ± 0.06. The moderate heritability estimates indicate the potential for selection using favourable combinations of test days throughout the lactation period. It was also observed that a high proportion of total variance was attributed to the animal's permanent environment. Positive genetic correlations were observed for adjacent TDMY values, while the correlations became less pronounced for more distant TDMY values. Considering better fitting of the lactation curve, the use of B-spline functions for genetic evaluation of Alpine × Beetal goats using RRM is recommended.
本研究旨在通过随机回归模型(RRM)对阿尔卑斯山羊×贝蒂克山羊杂交羊的泌乳曲线进行基因评估。目的是通过设计核心繁殖计划内的实际繁殖策略,估计第一次泌乳测试日产奶量(TDMY)的遗传参数。为了模拟泌乳曲线的变化,本研究使用了 25998 个 TDMY 记录。为了估计遗传参数,考察了正交勒让德多项式(LEG)和 B 样条(BS),以生成合适和简约的模型。采用单性状 RRM 技术进行分析。平均第一次泌乳 TDMY 为 1.22±0.03kg,在第 7 次测试日(TD)左右达到峰值产量(1.35±0.02kg)。本研究表明,B 样条模型在对阿尔卑斯山羊×贝蒂克奶山羊的遗传评估中具有优越性。最佳随机回归模型被确定为二次 B 样条函数,由六个节点表示中心趋势。该模型有效地捕捉了加性遗传影响、动物特定的永久环境效应(c)和 22 个不同类别的(异质)剩余方差的模式。在泌乳早期,加性方差和遗传力(h)估计值较低,但在研究的大部分泌乳阶段都适中,范围从 0.09±0.04 到 0.33±0.06。适度的遗传力估计值表明,在整个泌乳期通过选择有利的测试日组合进行选择是有可能的。还观察到,总方差的很大一部分归因于动物的永久环境。相邻 TDMY 值之间存在正遗传相关,而较远 TDMY 值之间的相关性则不那么明显。考虑到泌乳曲线拟合更好,建议使用 RRM 对阿尔卑斯山羊×贝蒂克山羊进行 B 样条函数的遗传评估。