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.
Keywords:
Avena sativa L; stepwise; rotation systems; sustainable agriculture
HIGHLIGHTS (MANDATORY)
Nitrogen adjustment at sowing and coverage increase oat productivity.
Topdressing nitrogen application is dependent on oat environment and phenology.
Fuzzy modeling is dependent on an adequate rule base structure.
Thumbnail
