Comparative Polynomial Modeling of Ross Breeder Egg Production Curves in South Australia

Egg production is a critical economic indicator in the Australian poultry industry, particularly for Ross breeder broilers. This study aims to evaluate and determine the most accurate mathematical model for representing the egg production curve of Ross breeders at Baiada Poultry, South Australia. Data from a 34 week production cycle (week 24 to 57) were analyzed using four polynomial regression models: quadratic, cubic, quartic, and quintic. The parameters evaluated include the rate of increase toward peak production, the persistence after the peak, and the coefficient of determination (R2) to measure model accuracy. Preliminary observations show that Ross breeders exhibit a sharp increase in production from week 24, reaching a peak at weeks 28 until 32, followed by a gradual decline. The results of this mathematical modeling are expected to provide a precise tool for poultry managers to predict annual yields, optimize culling ages, and improve economic projections. Comparison of the models indicates that while lower-degree polynomials offer simplicity, higher degree models such as quartic and quintic provide better fitment for the biological fluctuations inherent in Ross breeder performance.