Peruzzi, N. J. [UNESP]Scala, N. L. [UNESP]Macari, Marcos [UNESP]Furlan, Renato Luis [UNESP]Meyer, A. D. [UNESP]Fernandez-Alarcon, M. F. [UNESP]Kroetz Neto, F. L. [UNESP]Souza, F. A. [UNESP]2014-05-202014-05-202012-10-01Poultry Science. Savoy: Poultry Science Assoc Inc, v. 91, n. 10, p. 2710-2717, 2012.0032-5791http://hdl.handle.net/11449/1409Experimental studies have shown that hatching rate depends, among other factors, on the main physical characteristics of the eggs. The physical parameters used in our work were egg weight, eggshell thickness, egg sphericity, and yolk per albumen ratio. The relationships of these parameters in the incubation process were modeled by Fuzzy logic. The rules of the Fuzzy modeling were based on the analysis of the physical characteristics of the hatching eggs and the respective hatching rate using a commercial hatchery by applying a trapezoidal membership function into the modeling process. The implementations were performed in software. Aiming to compare the Fuzzy with a statistical modeling, the same data obtained in the commercial hatchery were analyzed using multiple linear regression. The estimated parameters of multiple linear regressions were based on a backward selection procedure. The results showed that the determination coefficient and the mean square error were higher using the Fuzzy method when compared with the statistical modeling. Furthermore, the predicted hatchability rates by Fuzzy Logic agreed with hatching rates obtained in the commercial hatchery.2710-2717engfuzzy logicregression modelhatching eggHatchabilityArtigo10.3382/ps.2011-01878WOS:000309196400040Acesso restrito571355857292666908064094841596420000-0001-9549-0329