Comparison of the 3-phase segmented linear regression and artificial neural network models to predict broiler hatchability

Abstract

SUMMARY The objective of this study was to compare the performance of an artificial neural network (ANN) model and a 3-phase segmented linear regression model to describe the relationship between flock age and hatchability in broiler breeder flocks. The predictive quality of these models was tested for an external validation set of 14 wk, randomly chosen from 39 wk. The accuracy of the models was determined by the r2 value, mean square error, bias, and Theil’s U-statistic parameters. The r2 values of the 3-phase segmented linear regression and ANN models were 0.4003 and 0.9984, respectively. Therefore, the ANN produced more accurate predictions of hatchability than the 3-phase segmented linear regression model. We conclude, based on the results of this study in commercial broiler breeder flocks, that hatchability is a function of flock age and that the relationship can be described by an ANN model.