Animal Science and Genetics, School of Agricultural Science/Tasmanian Institute of Agriculture, University of Tasmania, Private Bag 54 Hobart, TAS 7001, Australia.
Dairy Research Centre, Tasmanian Institute of Agriculture, PO Box 3532 Burnie, TAS 7320, Australia.
J Dairy Sci. 2012 Sep;95(9):5344-5356. doi: 10.3168/jds.2011-4663.
Fourteen lactation models were fitted to average and individual cow lactation data from pasture-based dairy systems in the Australian states of Victoria and Tasmania. The models included a new "log-quadratic" model, and a major objective was to evaluate and compare the performance of this model with the other models. Nine empirical and 5 mechanistic models were first fitted to average test-day milk yield of Holstein-Friesian dairy cows using the nonlinear procedure in SAS. Two additional semiparametric models were fitted using a linear model in ASReml. To investigate the influence of days to first test-day and the number of test-days, 5 of the best-fitting models were then fitted to individual cow lactation data. Model goodness of fit was evaluated using criteria such as the residual mean square, the distribution of residuals, the correlation between actual and predicted values, and the Wald-Wolfowitz runs test. Goodness of fit was similar in all but one of the models in terms of fitting average lactation but they differed in their ability to predict individual lactations. In particular, the widely used incomplete gamma model most displayed this failing. The new log-quadratic model was robust in fitting average and individual lactations, and was less affected by sampled data and more parsimonious in having only 3 parameters, each of which lends itself to biological interpretation.
14 个泌乳模型被拟合到来自澳大利亚维多利亚州和塔斯马尼亚州牧场奶牛系统的平均和个体奶牛泌乳数据。模型包括一个新的“对数二次”模型，主要目标是评估和比较该模型与其他模型的性能。首先使用 SAS 中的非线性过程拟合了 9 个经验和 5 个机械模型，以平均荷斯坦-弗里森奶牛的测试日牛奶产量。使用 ASReml 中的线性模型拟合了另外两个半参数模型。为了研究首次测试日天数和测试日数量的影响，然后将 5 个最佳拟合模型拟合到个体奶牛泌乳数据中。使用残差均方、残差分布、实际值和预测值之间的相关性以及 Wald-Wolfowitz 运行检验等标准评估模型拟合优度。在拟合平均泌乳方面，除了一个模型外，所有模型的拟合优度都相似，但它们在预测个体泌乳方面的能力有所不同。特别是广泛使用的不完全伽马模型最明显地存在这种缺陷。新的对数二次模型在拟合平均和个体泌乳方面具有稳健性，受抽样数据的影响较小，并且仅具有 3 个参数，每个参数都易于进行生物学解释，因此更加简洁。
