ABSTRACT Bell peppers are one of the most cultivated and consumed vegetables in Brazil, and their high production yield largely depends on the use of high-quality seedlings. Supplementary lighting using light-emitting diodes (LEDs) can help in the production of seedlings and improve their quality. This study aims to develop a fuzzy model to predict the agronomic parameters of bell pepper seedlings under different light intensities. Experimental data on the lighting levels and biometric responses of bell pepper seedlings were used to develop a fuzzy model, and the lighting levels defined in five sets were used as the input variable. The model was used to predict the output variables, namely the plant height, number of leaves, stem diameter, internode number, shoot fresh weight, and root fresh weight. The results indicated that the use of supplemental lighting at a level of 75 μmol m-2s-1 was the most beneficial, producing seedlings with more leaves, higher stem diameters, internode numbers, and fresh weights. The model error rates were satisfactory for the predicted values of all variables, demonstrating the usefulness of the fuzzy model for estimating the best lighting levels in the cultivation of bell pepper seedlings.

ABSTRACT Temperature variation in egg incubation can negatively affect the hatching time and weight gain of chicks, hence improving the incubator temperature accuracy can improve hatching rates. Controllers based on the fuzzy methodology have shown great potential for use in controlling incubator temperature variations. Therefore, the objective of this study is to develop and evaluate a fuzzy logic-based controller for egg incubation. Four identical incubators were configured: two with a fuzzy controller and two with a conventional controller. After evaluation and validation, a case study of the incubating eggs of free-range chickens was conducted on where 12 incubation cycles consisting of 20 eggs per incubator. The variables obtained include hatchability and electricity consumption. The results showed that the fuzzy logic-based controller maintained uniform internal temperature and a 10.68% saving on electricity usage when compared with the conventional controller. Thus, the fuzzy methodology has great potential for use in the incubation of free-range eggs.