Fuzzy modeling of coffee productivity under different irrigation depths, water deficit and temperature

Abstract

The coffee culture has great economic importance on the world stage, especially for Brazil. Considered one of the most traded commodities on the world's trading exchanges. Thus, the main objective of this study was to develop a system based on fuzzy rules to evaluate coffee productivity, using irrigation, soil water deficit and ambient temperature as the main production factors. The research was developed from searches of scientific data on the main variables for coffee production. The work was divided into two stages: the first in the scientific search for data collection and the second in the development of the fuzzy model. With this, it was parameterized that the input variables would be the temperature, the irrigation depth, and the water deficit of the soil and for the output variable the coffee productivity. Based on the model prediction, the fuzzy system showed which variable values are necessary for the best coffee productivity, by a set of rules involving the variation of water deficit (60%), temperature (30°C) and irrigation (300 mm), for a productivity of 24 sc ha-1. The performance of the fuzzy system was tested by comparing it with articles on the subject that relate coffee production with irrigation, water deficit and temperature of the environment and in almost all cases the model was efficient, reinforcing the assessment of the strength of the scheme, the analysis was extended to several scenarios relating the same three input variables.