ABSTRACT
Fuzzy logic can simulate wheat yield by nitrogen and temperature nonlinearity, validating the use of hydrogel biopolymer. The objective of this study is to adapt the fuzzy logic model to the simulation of nitrogen biomass and wheat grain yield and non-linearity of the maximum air temperature, under the conditions of use of the hydrogel biopolymer, in high and low N-residual release systems. The study was conducted in 2014 and 2015, in Augusto Pestana, RS, Brazil (28 ° 26 ‘30’ latitude S and 54 ° 0 ‘58’ longitude W). The experimental design was a randomized block design with four replications in 5 x 5 factorial, for hydrogel doses (0, 30, 60, 90 and 120 kg ha-1), added in the furrow next to the seed, and N-fertilizer doses. (0, 30, 60, 90 and 120 kg ha-1), applied at the phenological stage V3 (third expanded leaf) as top-dressing, respectively. The pertinence functions together with the quantitative and linguistic values for the input and output variables are suitable for the use of fuzzy logic in the wheat yield simulation. The fuzzy model made it possible to estimate the values of biomass and wheat grain yield by nitrogen and non-linearity of the maximum air temperature under the conditions of use of the hydrogel biopolymer in high and low N-residual release systems.
Key words:
Triticum aestivum; water stress; hydrogel; fuzzy logic
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PGo - Observed grain yield (kg ha-1); PGs - Simulated grain yield (kg ha-1); * Significant at p≤0,05 error by the F test; R² = coefficient of determination; CV - Coefficient of variation (%)
PBo - Observed biomass productivity (kg ha-1); PBs - Simulated biomass productivity (kg ha-1); * Significant at p≤0,05 error by the F test; R² = coefficient of determination; CV - Coefficient of variation (%)