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Short communication: Novel method to predict body weight of primiparous dairy cows throughout the lactation

机译:简短交流:预测整个泌乳期初产奶牛体重的新方法

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摘要

Body weight (BW) of dairy cows can be estimated using linear conformation traits (calculated BW; CBW), which are generally recorded only once during a lactation. However, predicted BW (PBW) throughout the lactation would be useful, e.g., at milk-recording dates allowing feed-intake prediction for advisory purposes. Therefore, a 2-step approach was developed to obtain PBW for each milk-recording date. In the first step, a random-regression test-day model was used with CBW as observations to predict PBW. The second step consisted in changing means and (co) variances of prior distributions for the additive genetic random effects of the test-day model by using priors derived from results of the first step to predict again PBW. A total of 25,061 CBW from 24,919 primiparous Holstein cows were computed using equations from literature. Using CBW as observations, PBW was then predicted over the whole lactation for 232,436 dates corresponding to 207,375 milk-recording dates and 25,061 classification dates. Results showed that using both steps (the 2-step approach) provided more accurate predictions than using only the first step (the one-step approach). Based on the results of this preliminary study, BW of dairy cows could be predicted throughout the lactation using this procedure. These predictions could be useful in milk-recording systems to compute traits of interest (e.g., feed-intake prediction). The developed novel method is also flexible because actual direct measurements of BW can also be used together with CBW, the prediction model being able to accommodate different levels of accuracies of used BW phenotypes.
机译:可以使用线性构象特征(计算​​的体重; CBW)估算奶牛的体重(BW),通常在泌乳期间仅记录一次。然而,整个泌乳期的预测体重(PBW)将是有用的,例如,在记录牛奶的日期,允许出于咨询目的预测饲料的摄入量。因此,开发了一种两步法来获取每个牛奶记录日期的PBW。第一步,将随机回归测试日模型与CBW结合使用,以观察预测PBW。第二步包括通过使用从第一步结果中得出的先验来再次预测PBW,来改变测试日模型的附加遗传随机效应的先验分布的均值和(协)方差。使用来自文献的方程,从24,919头初生荷斯坦奶牛中总共得到了25,061头体重。使用CBW作为观察值,然后在232,436个日期的整个哺乳期预测PBW,对应于207,375个奶记录日期和25,061个分类日期。结果表明,与仅使用第一步(单步法)相比,使用两个步骤(两步法)可提供更准确的预测。根据这项初步研究的结果,使用该程序可以预测整个泌乳期的奶牛体重。这些预测可能在牛奶记录系统中用于计算目标特征(例如,饲料摄入量预测)。所开发的新颖方法也很灵活,因为BW的实际直接测量值也可以与CBW一起使用,该预测模型能够适应所用BW表型的不同精确度。

著录项

  • 来源
    《Journal of dairy science》 |2015年第1期|692-697|共6页
  • 作者单位

    Animal Science Unit, Gembloux Agro-Bio Tech, University of Liege, B-5030 Gembloux, Belgium;

    Animal Science Unit, Gembloux Agro-Bio Tech, University of Liege, B-5030 Gembloux, Belgium,National Fund for Scientific Research, B-1000 Brussels, Belgium;

    Animal Science Unit, Gembloux Agro-Bio Tech, University of Liege, B-5030 Gembloux, Belgium,National Fund for Scientific Research, B-1000 Brussels, Belgium;

    Walloon Agricultural Research Centre, Production and Sectors Department, B-5030 Gembloux, Belgium;

    Animal Science Unit, Gembloux Agro-Bio Tech, University of Liege, B-5030 Gembloux, Belgium;

  • 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

    dairy cattle; body weight; feed intake; Bayesian prediction model;

    机译:乳牛;体重;采食量贝叶斯预测模型;
  • 入库时间 2022-08-17 23:23:31

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