Mathematical modeling for egg production and egg weight curves in a synthetic white leghorn

Abstract

This study was conducted to evaluate 8 mathematical models, namely, Logistic (LM), Morgqan Mercer Flodin (MMF), Polynomial Fit (PF), Rational Function (RF), Sinusoidal Fit (SF), Quadratic fit (QF), Gompertz function (GF), and Modification Compartmental Model (MCM) fitted to weekly egg production and egg weight of synthetic White Leghorn (SWL) population 21 to 40 wk of age of 5 generations (2015-16 to 2019-20). The relevant data for the present investigation were collected from SWL population, maintained in the department of Animal Genetics and Breeding, LUVAS, Hisar (India). The efficiency or reliability of the models were obtained by various criteria of goodness of fit such as coefficients of determination (R²), Root Mean Square Error (RMSE), Akaike's Information Criterion (AIC), Bayesian Information Criterion (BIC), graphical analysis, and Chi-square test. The results indicated that RF, MCM, SF, and PF were best models for fitting weekly egg production curve due to higher values of R² and low values of RMSE, AIC, and BIC as compare to remaining models. In case of weekly egg weight, the best values of goodness of fit criteria were showed by MMF model followed by MCM and LM model. The results indicated that these models could be conveniently used for fitting for weekly egg production and egg weight in synthetic white leghorn, respectively.

Keywords: egg production curves; mathematical models; synthetic White Leghorn.