Adjustment of nonlinear models and growth parameters and body nutrient deposition in meat-type and laying quail

Abstract

ABSTRACT The objective of this study was to determine the adjustment quality of non-linear models and estimate the growth parameters and body chemical composition of a meat-type quail strain (Coturnix coturnix coturnix) and two laying quail strains (Coturnix coturnix japonica), designated yellow and red. The study used 1500 quail, not sexed, distributed in a completely randomized design with three treatments and five repetitions. The experimental period was from 1-42 days of age. The birds were raised in a conventional system and fed ad libitum with a diet formulated to meet their nutritional requirements. Quail were weighed weekly, and a representative sample was slaughtered to evaluate their body chemical composition. The adjustment quality of the models was evaluated by means of the residual mean square (RMS), regression residue squares sum (SSRR), and number of iterations required for convergence. In evaluating the adjustment quality for the body weight of the three strains, the Gompertz, Logistic, and Von Bertalanffy models gave good fit, with Gompertz providing the best adjustment among them. For body composition, the Gompertz and Logistic models were the best, with Gompertz showing a slight superiority. Gompertz is the best model for describing growth curves and body chemical composition of body weight, protein, water, and ash in meat-type quail. In addition, it is the best model for describing growth curves and body chemical composition of body weight of yellow laying quail and of body weight, protein, and ash in red laying quail. Logistic was the best model for describing growth curves and body chemical composition of water, protein, and ash in yellow laying quail, and of water in red laying quail.

Keywords

• body chemical deposition
• Gompertz curve
• iterations
• residual mean square
• square sum of the regression residual