荷斯坦奶牛产奶性状遗传参数估计及育种方案优化

Estimation of Genetic Parameters of Milk Production Traits in Holstein Cows and Optimization of Breeding Plan

中文关键词: 中国荷斯坦奶牛  产奶性状  遗传参数  遗传进展

英文关键词: Chinese Holstein cows  milk production traits  genetic parameters  genetic progress

中文摘要:

      根据遗传参数和育种实际情况制定和优化育种方案，可以加快遗传进展，提高经济效益。本研究基于河北 3 个中型牧场 2996 头荷斯坦牛的 17173 条产奶记录（日产奶量、乳脂量、乳蛋白量、乳脂率、乳蛋白率）和系谱数据，用 SPSS 和 DMU 软件，通过一般线性模型解析非遗传因素（场别、产犊年份、产犊季节、产犊月龄、泌乳阶段）对产奶性状的影响，并利用最大似然估计（AI_REML）法估计方差组分及遗传参数，最后根据遗传参数调整不同育种参数，使用 SelAction 软件模拟计算日产奶量遗传进展，并结合成本收益设计优化育种方案。结果显示，产奶性状主要受场别、产犊年份、产犊季节、产犊月龄及泌乳阶段的影响；日产奶量、乳脂量、乳蛋白量的遗传力估计值分别为 0.450、0.230 和 0.380，但乳脂率、乳蛋白率的遗传力估计值仅为 0.043 和 0.054。基于以上遗传参数，仅采用系谱选择最佳线性无偏预测（BLUP）法，日产奶量遗传进展可达 0.8kg / 代左右，且可以对青年公牛进行早期选择，还不增加时间和测定成本。增加后代测定可加快遗传进展，增幅与后代测定数有关。

英文摘要:

      Effective breeding programs that incorporate both genetic parameters and practical constraints can enhance genetic improvement and economic returns in dairy production. Utilizing a total of 17174 milk production records (including daily milk yield, milk fat yield, milk protein yield, and corresponding percentages) and pedigree data collected from 2996 Holstein cows across three medium-sized farms in Hebei Province, SPSS and DMU software were employed to assess the impact of non-genetic factors on milk production traits using general linear models. Genetic variance components and heritability estimates were obtained using the AI-REML (Average Information Restricted Maximum Likelihood) method. Ultimately, breeding parameters were modified according to the genetic parameters, and genetic progress in daily milk production was simulated and calculated using SelAction software, and the breeding program was optimized based on a cost-benefit analysis. The findings indicated that milk production traits are predominantly influenced by field effects, calving year, season, month of age, and lactation stage. Heritability estimates were as follows: daily milk yield (0.450), milk fat yield (0.230), milk protein yield (0.380), milk fat percentage (0.043), and milk protein percentage (0.054). Based on these parameters, the implementation of BLUP (Best Linear Unbiased Prediction) selection strategies could result in a genetic gain of approximately 0.8kg in daily milk yield, without extending the selection cycle or increasing measurement costs. Furthermore, genetic gain was positively correlated with the number of progeny evaluated, emphasizing the efficiency of early sire selection in herd genetic improvement.