Fuzzy Modeling for a More Sustainable Nitrogen Management in Oat Crops

Abstract Meteorological conditions affect the dynamics of nitrogen (N) by oat crops. Fuzzy logic allows the development of simulation models involving N management and the non-linearity of meteorological conditions. The objective of this study was to identify the most sustainable N management for oat crops considering N rates applied at sowing and as top-dressing with different timing. Potential variables were selected for the development of a rule base for fuzzy modeling and simulate grain yield for N managements considering the non-linearity of meteorological conditions. The experiment was carried out in Augusto Pestana, RS, Brazil, from 2015 to 2017. A randomized block design with four replications was used, in a 4×3 factorial arrangement, consisted of four N rates applied at sowing (0, 10, 30 and 60 kg/ha), using total N top-dressing rates of 70 kg/ha for the soybean-oat and 100 kg/ha for the maize-oat, applied at three timings (10, 30, and 60 days after emergence). The most sustainable N managements for oat crops were under absence of N and application 10 kg/ha of N at sowing, with the remainder applied as top-dressing at 10 and 30 days after emergence. The N application timing, mean air temperature, and rainfall depth are potential variables for the development of a rule base for fuzzy modeling, and efficient in simulating oat grain yield.