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Critical Evaluation of Seven Lactation Curve Estimation Models

机译:七哺乳曲线估计模型的关键评估

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A mathematical model of the lactation curve approximation provides summary information about dairy cattle production, which is useful in making management and breeding decisions and in simulating a dairy enterprise. Several nonlinear regression models have been developed during the past decades. Unfortunately, there is no unique algorithm in literature. The question of choosing the best function is brought up. We tested seven such models (Gaines, Nelder, Ning-Yang, Marek-Zelinkova, McMillan, Papajesic-Bodero, Wood) using milk yield data of more than 5 000 lactation cycles. Non-linear approximations showed high level of confidence in all models. Critical limitations of individual approaches are discussed using data of several individual cows with problematic approximations. We stress the limitations of individual--generally well-fitting--mathematical models at the level of individual animals. The best results were obtained with Wood, Nelder or Marek-Zelinkova models.
机译:哺乳曲线近似的数学模型提供有关乳制品牛生产的摘要信息,可用于制定管理和育种决策和模拟乳制品企业。在过去的几十年中已经开发了几种非线性回归模型。不幸的是,文献中没有独特的算法。选择了选择最佳功能的问题。我们测试了七种这样的模型(盖恩,尼尔德,宁阳,MAREK-Zelinkova,McMillan,Papajesic-Bodero,Wood)使用超过5 000次哺乳期的牛奶产量数据。非线性近似显示所有模型的信心高。使用具有有问题近似的多个单个奶牛的数据讨论单个方法的关键限制。我们强调个人 - 一般良好的拟合 - 数学模型在各个动物的水平上的局限性。用木材,膝内或马拉克Zelinkova模型获得了最佳结果。

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