An economic activity with the magnitude of the poultry industry, which uses top line equipment, generally is lead to make decisions involving all production parameters, based in subjective criteria. The aim of this paper is to study the use of artificial neural networks to predict performance parameters in breeding birds, belonging to a South Brazilian poultry farm. Data from 11 broiler breeder flocks was recorded between November, 11th 1997 and October, 1st 1999. These data were processed by artificial neural networks. They corresponded to 273 data lines related to weekly recordings. The artificial neural networks models were compared and the best was selected, based on its determination coefficient, (R²), Mean Squared Error (QME), and by graphical analysis of the plot of network predictions versus the predictions minus the actual data. The authors conclude that it is possible to explain the performance parameters of breeding birds with the use of Artificial Neural Networks. The method allows decision making by the technical staff, based on objective criteria, scientifically obtained. Besides that, this method allows the simulation of consequences of these decisions and estimates the contribution of each variable used in the phenomena under study.
poultry; management; breeding; broiler breeders; artificial neural networks; artificial intelligence
