线性混合模型和值模型之间的比较,用于估计牛第一次分娩时的年龄和牛奶产量的差异组件
Raimundo Nonato Colares Camargo-Júnior1,2, Cláudio Vieira de Araújo3, Marina de Nadai Bonin Gomes4
1Postgraduate Program in Animal Science (PPGCAN), Institute of Veterinary Medicine, Federal University of Para (UFPA), Federal Rural University of the Amazon (UFRA), Brazilian Agricultural Research Corporation (EMBRAPA), Castanhal, Brazil.
与线性混合模型相比,门模型提供了更准确的基因评估,用于Murrah水牛在第一次分娩时的 sire年龄. 这种改进的准确性提高了育种价值的预测,而不会影响牛奶产量估计.
科学领域:
- 动物遗传学动物遗传学
- 量化遗传学 量化遗传学
- 畜牧养殖 畜牧养殖 畜牧养殖
背景情况:
- 在Murrah水牛中优化遗传评估需要整合牛奶产量, sire 遗传价值,以及第一次分娩时的年龄.
- 准确估计第一个分娩时的年龄差异组件对于有效的育种计划至关重要.
研究的目的:
- 将线性混合模型 (LMM) 与值模型 (TM) 进行比较,以估计Murrah水牛第一次分娩时的年龄差异组件.
- 使用这两种模型评估牛奶产量与初次分娩年龄之间的遗传关联.
- 评估每个模型对遗传评估的影响.
主要方法:
- 使用了Murrah水牛的数据集,包括总牛奶产量和第一次分娩时的年龄.
- 使用贝叶斯推理和吉布斯采样器对LMM (模型1) 和TM (模型2) 进行估计的方差元件.
- 模型2将牛奶产量与第一个产犊时的年龄结合起来进行分析.
主要成果:
- 牛奶产量与第一次分娩时的年龄之间的附加遗传相关性很低 (0.11对于LMM,0.17对于TM).
- 牛奶生产的育种价值在两种模型中都显示出极小的差异.
- 门模型 (模型2) 显示了第一次分娩时年龄的幅度降低,并提高了亲属的预测准确性,特别是那些具有负繁殖值的亲属.
结论:
- 值模型比线性混合模型更有效,用于分析Murrah水牛的第一个分娩时的年龄差异组件.
- 门模型提供了更准确的遗传价值估计,关于父亲的年龄在第一次分娩.
- 实施值模型不会对牛奶产量预测产生负面影响.
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