Adjusting weight growth curve of male quails &lt;i&gt;Coturnix japonica&lt;/i&gt; reared in the semi-arid region of the State of Pernambuco

Leandro Ricardo Rodrigues De Lucena,Marco Aurélio Carneiro De Holanda,Mônica Calixto Ribeiro De Holanda,Marcelo Lopes Dos Anjos

doi:10.4025/actascianimsci.v41i1.42563

Abstract

This study adjusted different regression models to describe the growth pattern of meat quails from birth to 42 days of age. Data of 300 male quails were used. Weight and height information of all quails were collected weekly from the 1st to the 42nd day of age. Body weight of poultry was subjected to the polynomial, logistic, Gompertz, Weibull, and log-normal regression models. The criteria used to choose the best model to explain the growth curve of quails were the coefficient of determination of the model, Akaike’s information criterion, sum of squared residuals and Willmott’s index. For all the models used, the variables age and height were significant to explain the weight of quails. The polynomial (R² = 99.99%, AIC = 24.68, SSR = 27.5, d = 0.9999) and log-normal (R² = 99.60%, AIC = -17.5, SSR = 107.15, d = 0.9989) models presented the best fit criteria and were recommended to explain the growth of quails.

Highlights

Coturniculture is a branch of poultry farming that has been highlighting in recent years (Drumond et al, 2013)
The present study aimed to evaluate the weight growth of quails from 1 to 42 days of age by fitting regression models
In the evaluation of Gompertz regression model, we verified that the model did not present good adjustments in relation to the weights observed, Figure 3

Summary

Introduction

Coturniculture is a branch of poultry farming that has been highlighting in recent years (Drumond et al, 2013). 41, e42563, 2019 they verified that Gompertz model was indicated as the most suitable to explain the weight growth of quails. Mota et al (2015) observed that the logistic model was the most weight growth to explain the weight of quails.

Results

Conclusion