Comparison of the Quality Adjusting of Nonlinear Models for Organs, Carcass and Body Components in Meat-Type (Coturnix Coturnix Coturnix) and Laying-Type (Coturnix Coturnix Japonica) Quail

ABSTRACT The objective of this study was to evaluate the adjustment quality of nonlinear models to data organs growth, carcass and body components of meat-type (Coturnix coturnix coturnix) and japanese laying-type (Coturnix coturnix japonica) quail. A total of 1350 quails from one to 42 d old were distributed in a completely randomized design, with five replicates each. To determine the organs growth (gut, heart, liver and gizzard), carcass and body components (wing, thigh and drumstick, back and breast), two quails per repetition were slaughtered weekly. The data were evaluated in function of different nonlinear models (Logistical, Brody, Richards, Von Bertalanffy and Gompertz). All models studied adjusted the data, differing in adjustment quality. Brody model showed the best description of gut length to all treatments. For the data gizzard weight, heart, liver and gut, the models that best adjusted, presenting smaller residual mean square and numbers iterations were Gompertz and Logistical. The Gompertz, Logistic and Von Bertalanffy models were the most adequate to describe the thigh and drumstick growth, back and breast, and Gompertz models and Logistic to describe the wing growth and carcass, showing lesser number of iterations to achieve the convergence of date, as well as low residual mean square and squares sums of the regression residuals. The Gompertz model was the most appropriate to describe the organs growth and body components in meat- and laying-type quail when evaluated in growth phase.

摘要：本研究旨在评估非线性模型（nonlinear models）对肉用型鹌鹑（Coturnix coturnix coturnix）与蛋用型日本鹌鹑（Coturnix coturnix japonica）的器官生长、胴体及体组成数据的拟合质量。本试验共选取1350只1至42日龄的鹌鹑，采用完全随机设计（completely randomized design），设置5个重复组。为测定器官生长（肠道、心脏、肝脏与肌胃）及体组成（翅、腿胫、背部与胸部）指标，每周从每个重复组中选取2只鹌鹑进行屠宰。采用Logistical、Brody、Richards、Von Bertalanffy及Gompertz等多种非线性模型对数据进行拟合分析。所有供试模型均可对数据进行拟合，但拟合质量存在差异。其中，Brody模型对所有处理组的肠道长度数据拟合效果最优。针对肌胃重量、心脏、肝脏及肠道重量数据，拟合效果最佳、残差均方（residual mean square）与迭代次数均最小的模型为Gompertz与Logistical模型。Gompertz、Logistic及Von Bertalanffy模型最适于描述腿胫、背部及胸部的生长情况；Gompertz模型与Logistical模型则最适于描述翅生长与胴体指标，其达到数据收敛所需的迭代次数更少，且残差均方与回归残差平方和（squares sums of the regression residuals）均较低。在生长阶段评估中，Gompertz模型是描述肉用型与蛋用型鹌鹑器官生长及体组成的最优模型。