Egg production curves and their prediction through mathematical models in a random-bred broiler breeder control population

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

“…This result was in conformity with the findings of various research workers who adopted different models in layer type chicken viz., Gavora et al (1982) , Cason and Britton (1988) , Lal et al (2003) , Narinc et al (2010) , and Savegnago et al (2012) . Similar to present results, Abraham and Murthy (2017) studied 6 mathematical models for egg number, namely, Logistic, MMF, Polynomial Fit, Rational Function, Sinusoidal Fit, and Quadratic fit and they reported Rational Function (R 2 : 94.08–97.22%) and Polynomial Fit (R 2 : 93.26–96.67%) as the best fitting models. On the other hand, Thomas et al (1994) reported QF as best model for egg production curve in layers.…”

“…Use of mathematical models to accurately fit egg production curves is necessary to make economic projections for laying hens ( Adams and Bell, 1980 ; Kiran, 1998 ). It is also of great importance in practical poultry breeding for making predictions about egg production on an annual or any other chosen period basis, to facilitate early selection of the breeder birds ( Bindya et al, 2010 , Abraham and Murthy, 2017 ; Ahmadu et al, 2017 ). Most of the nonlinear models presented in the literature to fit egg production can have curve parameters with a biological interpretation, which makes it possible to summarize in 3 or 4 parameters what the egg production pattern is like.…”