Abstract
This study aimed to compare fuzzy systems with different configurations to predict the surface temperature (ts) of broiler chickens subjected to different intensities and durations of thermal challenges in the second week of life. Data on the ts of broiler chickens aged 8 to 11 days were acquired by infrared thermography and subjected to combinations of four dry-bulb temperatures (tdb) (24, 27, 30, and 33 °C) and four durations of thermal challenges (DTC) (1, 2, 3, or 4 days). The input variables of the fuzzy systems were tdb and DTC, and the output variable was ts. The Mamdani inference method involving five defuzzification methods [center of gravity (centroid), bisector of the area (bisector), largest of maximum (lom), middle of maximum (mom), and smallest of maximum (som)], and Sugeno inference with two defuzzification methods [weighted average (wtaver) and weighted sum (wtsum)] were evaluated. For both inference methods, triangular and Gaussian pertinence functions were tested for input and output variables, except for Sugeno inference, which used singletons functions as output variables. While developing fuzzy systems, different configurations must be compared, and the system with smaller simulation errors should be selected.
Highlights
The thermal environment affects poultry production in Brazil and is a challenge to the application of confinement techniques because of the large territorial extension of the country (Ferraz et al, 2014)
This study focused on comparing fuzzy systems with different configurations to predict the surface temperature of broiler chickens subjected to different intensities and times of thermal treatment in the second week of life
In the first three weeks of life, the maintenance of thermal comfort conditions is essential in broiler chickens, and ts varies as a function of tdb (Abreu et al, 2012)
Summary
The thermal environment affects poultry production in Brazil and is a challenge to the application of confinement techniques because of the large territorial extension of the country (Ferraz et al, 2014). Air temperature and relative humidity are the most relevant to poultry because they affect the control of body temperature and heat exchange for maintaining homeothermy (Costa et al, 2012; Ferreira et al 2012). Energy expenditure to maintain homeothermy leads to physiological changes in the surface temperature of birds and compromises animal performance (Oliveira et al, 2006). Surface temperature is a rapid response to discomfort caused by changes in ambient temperature (Dahlke et al, 2005)
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