Departamento de Ciências Exatas, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, 14884-900, Via de Acesso Prof. Paulo Donato Castellane s/n, Jaboticabal, São Paulo, Brazil.
Poult Sci. 2013 Jan;92(1):277-82. doi: 10.3382/ps.2012-02380.
The objective of this study was to fit growth curves using nonlinear and linear functions to describe the growth of ostriches in a Brazilian population. The data set consisted of 112 animals with BW measurements from hatching to 383 d of age. Two nonlinear growth functions (Gompertz and logistic) and a third-order polynomial function were applied. The parameters for the models were estimated using the least-squares method and Gauss-Newton algorithm. The goodness-of-fit of the models was assessed using R(2) and the Akaike information criterion. The R(2) calculated for the logistic growth model was 0.945 for hens and 0.928 for cockerels and for the Gompertz growth model, 0.938 for hens and 0.924 for cockerels. The third-order polynomial fit gave R(2) of 0.938 for hens and 0.924 for cockerels. Among the Akaike information criterion calculations, the logistic growth model presented the lowest values in this study, both for hens and for cockerels. Nonlinear models are more appropriate for describing the sigmoid nature of ostrich growth.
本研究旨在通过非线性和线性函数拟合生长曲线,以描述巴西鸵鸟种群的生长情况。数据集包含了 112 只鸵鸟,从孵化到 383 日龄的体重测量值。应用了两种非线性生长函数(Gompertz 和 logistic)和三阶多项式函数。使用最小二乘法和高斯牛顿算法估计模型参数。通过 R² 和赤池信息量准则评估模型的拟合优度。logistic 生长模型的 R² 为母鸡的 0.945 和公鸡的 0.928,Gompertz 生长模型的 R² 为母鸡的 0.938 和公鸡的 0.924。三阶多项式拟合的 R² 为母鸡的 0.938 和公鸡的 0.924。在赤池信息量准则的计算中,logistic 生长模型在本研究中无论是对母鸡还是公鸡,都呈现出最低的值。非线性模型更适合描述鸵鸟生长的 S 型曲线。