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Genetic parameters of total milk yield and factors describing the shape of lactation curve in dairy buffaloes

机译:乳牛的总产奶量的遗传参数和描述泌乳曲线形状的因素

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摘要

The objective of this study was to apply factor analysis to describe lactation curves in dairy buffaloes in order to estimate the phenotypic and genetic association between common latent factors and cumulative milk yield. A total of 31 257 monthly test-day milk yield records from buffaloes belonging to herds located in the state of Sao Paulo were used to estimate two common latent factors, which were then analysed in a multi-trait animal model for estimating genetic parameters. Estimates of (co)variance components for the two common latent factors and cumulated 270-d milk yield were obtained by Bayesian inference using a multiple trait animal model. Contemporary group, number of milkings per day (two levels) and age of buffalo cow at calving (linear and quadratic) as covariate were included in the model as fixed effects. The additive genetic, permanent environmental and residual effects were included as random effects. The first common latent factor (F1) was associated with persistency of lactation and the second common latent factor (F2) with the level of production in early lactation. Heritability estimates for F1 and F2 were 0·12 and 0·07, respectively. Genetic correlation estimates between F1 and F2 with cumulative milk yield were positive and moderate (0·63 and 0·52). Multivariate statistics employing factor analysis allowed the extraction of two variables (latent factors) that described the shape of the lactation curve. It is expected that the response to selection to increase lactation persistency is higher than the response obtained from selecting animals to increase lactation peak. Selection for higher total milk yield would result in a favourable correlated response to increase the level of production in early lactation and the lactation persistency.
机译:这项研究的目的是应用因子分析来描述水牛的泌乳曲线,以便估计常见潜在因子与累积奶产量之间的表型和遗传关联。来自圣保罗州牛群的水牛总共31 257个测试日的月产奶量记录用于估算两个共同的潜在因素,然后在多性状动物模型中对其进行分析以估算遗传参数。使用多重性状动物模型通过贝叶斯推断获得两个共同潜在因子的(协)方差分量以及累计的270天奶产量。作为固定效应,模型包括当代组,每天挤奶次数(两个级别)和产犊时水牛的年龄(线性和二次)作为协变量。遗传效应,永久性环境效应和残留效应的累加也包括在随机效应中。第一个共同的潜在因子(F1)与哺乳期的持续性有关,第二个共同的潜在因子(F2)与早期哺乳期的生产水平相关。 F1和F2的遗传力估计分别为0·12和0·07。 F1和F2与累积产奶量之间的遗传相关性估计为正和中等(0·63和0·52)。采用因子分析的多变量统计数据允许提取两个描述泌乳曲线形状的变量(潜在因子)。预期对选择增加泌乳持续性的反应高于选择动物对增加泌乳峰的反应。选择较高的总产奶量将导致良好的相关响应,从而增加早期泌乳和泌乳持续时间的生产水平。

著录项

  • 来源
    《Journal of dairy research》 |2012年第1期|p.60-65|共6页
  • 作者单位

    Department of Animal Science, Sao Paulo State University (FCAV/UNESP), Jaboticabal, SP, Brazil, 14884 900;

    Department of Animal Science, Sao Paulo State University (FCAV/UNESP), Jaboticabal, SP, Brazil, 14884 900;

    Department of Animal Science, Sao Paulo State University (FCAV/UNESP), Jaboticabal, SP, Brazil, 14884 900;

    Department of Animal Science, Sao Paulo State University (FCAV/UNESP), Jaboticabal, SP, Brazil, 14884 900,Conselho Nacional de Desenvolvimento Cientffico e Tecnologico (CNPq) and Institute Nacional de Ciencia e Tecnologia -Ciencia Animal (INCT- CA), Vicosa, MG, Brazil, 36570 000;

    Universidad Nacional Agraria de la Selva, Aptdo. 156, UNAS-Tingo Maria-Peru;

    Department of Animal Science, Sao Paulo State University (FCAV/UNESP), Jaboticabal, SP, Brazil, 14884 900,Conselho Nacional de Desenvolvimento Cientffico e Tecnologico (CNPq) and Institute Nacional de Ciencia e Tecnologia -Ciencia Animal (INCT- CA), Vicosa, MG, Brazil, 36570 000;

  • 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

    multivariate analysis; gibbs sampler; buffaloes; genetic parameters; milk yield;

    机译:多元分析吉布斯采样器水牛遗传参数牛奶产量;

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