Using non-linear models to describe growth curves for Thai black-bone chickens

Abstract

Importance of the work: Modelling the growth curve of a chicken line is important for optimizing the management for both broiler and layer chickens. In the present study, a non-linear model was developed to estimate growth in a Thai black-bone chicken population.
Objectives: To determine an appropriate non-linear model to describe the growth curve in Thai black-bone chickens.
Materials & Methods: Individual body weights from 3,280 birds were collected at ages 0 wk, 2 wk, 4 wk, 6 wk, 8 wk, 10 wk and 12 wk. Three non-linear growth models (Gompertz, logistic, von Bertalanffy) were implemented using the Levenberg-Marquardt algorithm. The coefficient of determination (R2), root mean squared error (RMSE) and mean absolute error (MAE) were used to determine the most appropriate model.
Results: Growth curves between male and female chickens were significantly (p < 0.05) different; the males grew faster than the females. The von Bertalanffy model provided the best fit for the growth curves in male and female chickens based on R2, RMSE
and MAE values. However, the R2 values from the three non-linear growth models
were all close to 1 (R2 > 0.9). Hence, all models described very well the growth curves from day 0 to age 12 wk for black-bone male and female chickens.
Main findings: The results indicated that the three non-linear functions could be used to model growth in black-bone chickens. Further studies for the development of breeding programs are required that include genetic parameters in growth curve modeling and their relationships with other economically important traits.