Fuzzy model for predicting cloacal temperature of broiler chickens under thermal stress

Abstract

Broiler chickens submitted to different intensities and durations of thermal stress are subject to variation in cloacal temperature and, consequently, to a decrease in performance. Given the complexity of these interactions, artificial intelligence is a useful methodology for decision-making. Thus, this study aimed to assess and predict, by means of a fuzzy model, the cloacal temperature of broiler chickens submitted to thermal stress in the second week of life, with varying durations and intensities, in climatized wind tunnels. Mamdani's inference and defuzzification methods by means of the center of gravity were used. One hundred and twenty rules were elaborated. The developed fuzzy model was used to predict the cloacal temperature of broiler chickens on the day of thermal stress as a function of air dry-bulb temperature (°C), stress duration (days), and the number of days after thermal stress. Cloacal temperature values simulated by the fuzzy model showed standard deviations and percentage errors lower than 0.02 and 0.08%, respectively, when compared to those obtained experimentally.