在使用不同测试日模型的白马丽扎羊品种中,基因参数估计了牛奶产量
Petya Zhelyazkova1, Doytcho Dimov1, Sreten Andonov2,3
1Department of Animal Sciences, Agricultural University, Plovdiv, Bulgaria.
Archives animal breeding
|November 29, 2023
概括
可重复性模型提供了更好的复杂性和适应性平衡,用于估计白马丽扎羊的测试日牛奶产量的遗传参数. 与随机回归模型相比,这些模型显示出较小的预测误差.
科学领域:
- 动物遗传学和动物繁殖
- 量化遗传学 量化遗传学
- 绵羊生产 绵羊生产
背景情况:
- 白玛丽扎羊品种是保加利亚的多用途本土品种,对遗传学研究至关重要.
- 对测试日牛奶产量 (TDMY) 的基因参数的准确估计对于育种计划至关重要.
- 之前的研究已经探索了各种线性模型,但对TDMY的最佳模型选择仍然是一个感兴趣的领域.
研究的目的:
- 为了估计白马丽萨羊群中测试日奶产 (TDMY) 的遗传参数.
- 确定最合适的线性模型来准确估计TDMY的遗传参数.
主要方法:
- 利用了来自987只母羊 (1992-2015年) 的8768个TDMY记录的数据集.
- 制定并测试了九个测试日模型 (TDM):三个可重复性模型 (REP) 和六个随机回归模型 (RRM),包括使用阿里和谢弗回归的模型.
- 使用可遗传性,可重复性系数,Akaike信息标准 (AIC),贝叶斯信息标准 (BIC) 和日志概率 (LogL) 的评估模型.
主要成果:
- 可重复性模型 (REP1,REP2,REP3) 产生了一致的可遗传性 (大约. 0.35) 和可重复性 (大约. 0.38) 的估计.
- 随机回归模型 (RRMs) 显示了哺乳曲线轨迹的差异,第三阶多项式显示了更多的遗传多样性,但更高的AIC,BIC和LogL.
- 可重复性模型展示了模型复杂性和数据适应性之间的优越平衡,与RRMs相比,预测错误较低.
结论:
- 建议使用可重复性模型来估计白马丽扎羊中TDMY的遗传参数,因为它们更好地适应和更准确地预测.
- 虽然RRM可以揭示更多的遗传多样性,但它们的复杂性和相关的信息标准表明它们对这个特定的数据集不太理想.
- 这些发现为优化白马丽扎羊群的遗传选择策略提供了宝贵的见解.
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