1Laboratório de Zootecnia,Centro de Ciências e Tecnologias Agropecuárias (CCTA),Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF),Av. Alberto Lamego 2000,Campos dos Goytacazes,RJ,CEP 28013-602,Brazil.
2Animal Science Graduate Program,CCTA/UENF,Campos dos Goytacazes, RJ, CEP 28013-602,Brazil.
Animal. 2018 Mar;12(3):538-553. doi: 10.1017/S1751731117001884. Epub 2017 Aug 3.
We studied the ontogenetic growth of goat wethers (castrated male goats) of the Saanen and Swiss Alpine breeds based on a large range of intraspecific body mass (BM). The body parts and the chemical constituents of the empty body were described by the allometric function by using BM and the empty body mass (EBM) as the predictors for morphological traits and chemical composition, respectively. We fitted the allometric scaling function by applying the SAS NLMIXED procedure, but to evaluate assumptions regarding variances in morphological and compositional traits, we combined the scaling function with homoscedastic (MOD1), and the heteroscedastic exponential (MOD2) and power-of-the-mean (MOD3) variance functions. We also predicted the ontogenetic growth by using the traditional log-log transformation and back-transformed results into the arithmetic scale (MOD4). We obtained predictions from MOD4 in the arithmetic scale by a two-step process, and evaluated MOD1, MOD2 and MOD3 by a model selection framework, and compared MOD4 with MOD1, MOD2 and MOD3 based on goodness-of-fit measures. Based on information criteria for model selection, heterogeneous variance functions were more likely to describe 10 over 36 traits with a low level of model selection uncertainty. One trait was predicted by averaging the MOD1 and MOD2 variance functions; and nine traits were better described by averaging the MOD2 and MOD3 variance functions. The predictions for other 16 traits were averaged from MOD1, MOD2 and MOD3. However, MOD4 better described 11 traits according to the goodness-of-fit measures. Depending on the variable being analyzed, the body parts and the chemical amounts exhibited the three types of allometric behavior with respect to BM and EBM, that is, positive, negative and isometric ontogenetic growth. Reference BMs, that is, 20, 27, 35 and 45 kg, were used to compute the net protein and energy requirements based on the first derivative of the scaling function, and the results were presented in reference to the EBM and EBM0.75. Both the net protein and energy requirements scaled to EBM0.75 increased from 20 to 45 kg of BM.
我们基于大范围内的种内体重(BW),研究了萨能奶山羊和瑞士阿尔卑斯奶山羊去势公羊的个体生长发育。利用 BW 和空腹体重(EBW)作为形态特征和化学成分的预测因子,通过对体成分的体节函数描述了体成分和空体成分。我们通过应用 SAS NLMIXED 程序来拟合等比缩放函数,但为了评估形态和组成特征的方差假设,我们将缩放函数与同方差(MOD1)、异方差指数(MOD2)和均数幂(MOD3)方差函数相结合。我们还使用传统的对数-对数变换预测了个体生长发育,并将回归结果转换为算术标度(MOD4)。我们通过两步过程从算术标度的 MOD4 中获得预测值,并通过模型选择框架评估 MOD1、MOD2 和 MOD3,并根据拟合优度指标比较 MOD4 与 MOD1、MOD2 和 MOD3。基于模型选择的信息准则,异方差函数更有可能描述 10 个具有低模型选择不确定性的特征。一个特征是通过对 MOD1 和 MOD2 方差函数进行平均来预测的;另外 9 个特征通过对 MOD2 和 MOD3 方差函数进行平均来更好地描述。其他 16 个特征的预测值是从 MOD1、MOD2 和 MOD3 中平均得到的。然而,根据拟合优度指标,MOD4 更好地描述了 11 个特征。根据分析的变量,体成分和化学物质与 BW 和 EBW 呈三种类型的等比生长发育,即正、负和等生长发育。参考 BW 为 20、27、35 和 45kg,用于根据缩放函数的一阶导数计算净蛋白和能量需求,并以 EBW 和 EBW0.75 为参考表示结果。以 EBW0.75 为单位的净蛋白和能量需求均从 20kg 到 45kg 的 BW 增加。