The determination of livestock growth patterns is important for meat or milk production systems, and nonlinear models are used to summarize and interpret the information. The aim of this study was to more accurately estimate growth curve parameters in buffalo cows by evaluating and selecting nonlinear mixed models that employ different types of residuals and include or not contemporary groups (CG) as a covariate. Weight records from 720 animals obtained over a period of 60 months were used. The growth curves were fit using nonlinear mixed-effects models. The Bertalanffy, Gompertz and Logistic models were evaluated. Modelling residuals using four structures (constant, combined, exponential and proportional) and the inclusion or not of CG in the models were also evaluated. The Akaike information criterion (AIC) and Bayesian information criterion (BIC) were used to select the model. In addition to estimating the parameters of the nonlinear growth models and their correlations, the instantaneous growth rate and inflection point were obtained. The Bertalanffy model with a combined residual structure and CG exhibited the lowest AIC and BIC values. Asymptotic weight (A) estimates ranged from 621.8 to 742.1 kg, and the maturity rate (k) ranged from 0.068 to 0.115 kg/month. The correlation between A and k ranged from −0.32 to −0.82 among the models evaluated. The selection criteria indicated that the Bertalanffy model was the most suitable for growth curve analysis in buffaloes.

中文翻译：

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奶牛生长曲线非线性混合模型的选择（Bubalus bubalis）

牲畜生长模式的确定对于肉类或牛奶生产系统很重要，非线性模型用于总结和解释信息。本研究的目的是通过评估和选择非线性混合模型来更准确地估计水牛的生长曲线参数，这些模型采用不同类型的残差并且包括或不包括当代群体 (CG) 作为协变量。使用了 60 个月内获得的 720 只动物的体重记录。使用非线性混合效应模型拟合生长曲线。评估了 Bertalanffy、Gompertz 和 Logistic 模型。还评估了使用四种结构（常数、组合、指数和比例）建模残差以及模型中是否包含 CG。Akaike信息准则（AIC）和贝叶斯信息准则（BIC）用于选择模型。除了估计非线性增长模型的参数及其相关性外，还获得了瞬时增长率和拐点。具有组合残差结构和 CG 的 Bertalanffy 模型表现出最低的 AIC 和 BIC 值。渐近权重 (一种) 估计范围为 621.8 至 742.1 公斤，成熟率 (ķ) 范围为 0.068 至 0.115 公斤/月。之间的相关性一种和ķ在评估的模型中，范围从 -0.32 到 -0.82。选择标准表明，Bertalanffy 模型最适合水牛的生长曲线分析。