Fuzzy decision support system for improving the crop productivity and efficient use of fertilizers

This work investigates the process of reducing the fertilizer consumption and improving the crop productivity using the fuzzy logic systems. The system comprises two parts; land report based expert knowledge to stimulate the yield potential through appropriate organic lacking minerals in soil. The system structure consists of 8 parallel systems. The integrated knowledge and formation of fuzzy rules were based on multiple domain cores professionals - water, soil and agronomy with expert farmer interviews. This research work is to improve the productivity with minimum consumption of fertilizer. The study has been carried out to access the fertilizer consumption in both the ACZ(Agro Climatic Zone) with an exhaustive daily filed measurements and lab analysis for a duration of three years to determine exact fertilizer need for every individual lands. The above data was analysed in MATLAB to establish feasibility rules for decision support systems for the crops to get the targeted output.