Modeling of individual egg weights of Lohmann-Brown layer hens

Abstract

This study was carried out to determine the most suitable model for egg weights of the Cubic, Gompertz, Logistics, Gamma, Richard, Piecewise Quadratic, Orscov, and Sigmoaidal models, which are widely used in estimation. Lohmann-Brown Classic laying hens raised in Ondokuz Mayis University Research and Application farm were used as animal material. In the modeling of egg weights of 351 layer hens raised in 3-storey cages, individual egg weight data measured at weekly intervals, 32 on the 1st floor, 17 on the 2nd floor, and 27 on the 3rd floor, were taken into account, and a total of 76 hens' individual egg weight modeling was carried out. Coefficient of determination, mean square error, Durbin-Watson, and Akaike Information Criteria values were taken into account in modeling egg weights and comparing the compatibility of models with point distribution. According to the comparison criteria, it was determined that the best estimation model was Richard. It was determined that the closest predictions to the Richard prediction model were obtai-ned from the Logistics and Gompertz models. In addition, it was concluded that Orskov, Sigmoidal, and Quadratic piecewise regression models had the worst fit.