ABSTRACT
Fuzzy logic can simulate wheat productivity by assisting crop predictability. The objective of the study is the use of fuzzy logic to simulate wheat yield in the conditions of nitrogen use, together with the effects of air temperature and rainfall, in the main cereal succession systems in Southern Brazil. The study was conducted in the years 2014, 2015 and 2016, in Augusto Pestana, RS, Brazil. The experimental design was a randomized block design with four repetitions in a 4 x 3 factorial scheme for N-fertilizer doses (0, 30, 60, 120 kg ha-1) and nutrient supply forms [100% in phenological stage V3 (third expanded leaf); (70%/30%) in the phenological stage V3/V6 (third and sixth expanded leaf) and; fractionated (70%/30%) at the phenological stage V3/E (third expanded leaf and beginning of grain filling)], respectively, in the soybean/wheat and corn/wheat systems. The pertinence functions and the linguistic values established for the input and output variables are adequate for the use of fuzzy logic. Fuzzy logic simulates wheat grain yield efficiently in the conditions of nitrogen use with air temperature and rainfall in crop systems.
Key words:
Triticum aestivum; temperature; precipitation; fuzzy logic; modeling
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V3 - Full condition (100%) of the nitrogen dose in the third expanded leaf. V3/V6 - Fractionated condition (70%/30%) of the nitrogen dose in the third and sixth expanded leaf; V3/E - Fractionated condition (70%/30%) of the nitrogen dose in the third expanded leaf and initiation of grain filling
* Significant of p ≤ 0.05 by F testV3-Full condition (100%) of the nitrogen dose in the third expanded leaf; V3/V6-Fractional condition (70%/30%) of the nitrogen dose in the third and sixth expanded leaf; V3/E - Fractionated condition (70%/30%) of nitrogen dose in the third expanded leaf and initiation of grain filling; PGo - Observed grain yield (kg ha-1); PGe - Estimated grain yield (kg ha-1); *Significant at p ≤ 0.05 by the F test; R² - Coefficient of determination; CV - Coefficient of variation