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Relationships between milk yield and somatic cell score in Canadian Holsteins from simultaneous and recursive random regression models

机译:基于同时和递归随机回归模型的加拿大荷斯坦牛乳产量与体细胞评分之间的关​​系

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摘要

Multiple-trait random regression animal models with simultaneous and recursive links between phenotypes for milk yield and somatic cell score (SCS) on the same test day were fitted to Canadian Holstein data. All models included fixed herd test-day effects and fixed regressions within region-age at calving-season of calving classes, and animal additive genetic and permanent environmental regressions with random coefficients. Regressions were Legendre polynomials of order 4 on a scale from 5 to 305 d in milk (DIM). Bayesian methods via Gibbs sampling were used for the estimation of model parameters. Heterogeneity of structural coefficients was modeled across (the first 3 lactations) and within (4 DIM intervals) lactation. Model comparisons in terms of Bayes factors indicated the superiority of simultaneous models over the standard multiple-trait model and recursive parameterizations. A moderate heterogeneous (both across- and within-lactation) negative effect of SCS on milk yield (from -0.36 for 116 to 265 DIM in lactation 1 to -0.81 for 5 to 45 DIM in lactation 3) and a smaller positive reciprocal effect of SCS on milk yield (from 0.007 for 5 to 45 DIM in lactation 2 to 0.023 for 46 to 115 DIM in lactation 3) were estimated in the most plausible specification. No noticeable differences among models were detected for genetic and environmental variances and genetic parameters for the first 2 regression coefficients. The curves of genetic and permanent environmental variances, heritabilities, and genetic and phenotypic correlations between milk yield and SCS on a daily basis were different for different models. Rankings of bulls and cows for 305-d milk yield, average daily SCS, and milk lactation persistency remained the same among models. No apparent benefits are expected from fitting causal phenotypic relationships between milk yield and SCS on the same test day in the random regression test-day model for genetic evaluation purposes.
机译:在同一测试日,多特征随机回归动物模型在牛奶产量和体细胞评分(SCS)的表型之间具有同时和递归的联系,适用于加拿大Holstein数据。所有模型都包括产犊季节产犊季节的固定牛群试验日效应和区域年龄内的固定回归,以及具有随机系数的动物累加遗传和永久环境回归。回归是牛奶(DIM)中从5到305 d的4阶勒让德多项式。通过吉布斯采样的贝叶斯方法用于模型参数的估计。在整个泌乳期(前3次哺乳)和(4个DIM间隔内)对结构系数的异质性进行建模。关于贝叶斯因素的模型比较表明,同时模型优于标准的多特征模型和递归参数化。 SCS对牛奶产量的中度异质性(全乳期和全乳期)负面影响(哺乳期1的116至265 DIM为-0.36,哺乳期3至5-45 DIM的为-0.81)和在最合理的规格中,估算了牛奶产量的SCS(泌乳期为5到45 DIM的0.007,泌乳期3为46到115 DIM的0.023,乳汁的最高产值)。在前两个回归系数的遗传和环境差异以及遗传参数中,模型之间未发现明显差异。对于不同的模型,每天的遗传和永久环境差异,遗传力以及奶产量和SCS之间的遗传和表型相关关系曲线是不同的。在305天的产奶量,平均每日SCS和泌乳持久性方面,各模型的公牛和母牛排名保持不变。出于遗传评估目的,在随机回归测试日模型中,在同一测试日拟合牛奶产量与SCS之间的因果表型关系,预期不会带来明显的好处。

著录项

  • 来源
    《Journal of dairy science》 |2010年第3期|p.1216-1233|共18页
  • 作者单位

    Centre for Genetic Improvement of Livestock, Department of Animal and Poultry Science, University of Guelph, Guelph, Ontario, Canada, N1G 2W1;

    Centre for Genetic Improvement of Livestock, Department of Animal and Poultry Science, University of Guelph, Guelph, Ontario, Canada, N1G 2W1;

    Centre for Genetic Improvement of Livestock, Department of Animal and Poultry Science, University of Guelph, Guelph, Ontario, Canada, N1G 2W1;

  • 收录信息 美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    milk yield; somatic cell score; random regression; structural equation model;

    机译:牛奶产量体细胞评分随机回归结构方程模型;
  • 入库时间 2022-08-17 23:24:47

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