Fuzzy Logic-Based Crop Diversification to Increase Crop Yield

Nowadays, farmers are facing a major loss in crop production due to various reasons such as reduction in soil fertility, lack of irrigation facilities, lack of adequate knowledge on the suitable crop for the persisting soil. A variety of technological and infrastructural variables have an impact on crop diversity. Crop diversification has an impact on productivity, according to the findings. Economic considerations are having an ever-growing impact on Indian agriculture. This shouldn't come as a surprise because improving infrastructure, expanding irrigation, reaching remote markets, developing drought-resistant crops, and spreading these technologies have all reduced the influence of non-economic variables on even small farmers’ crop selection. In this paper we attempt to predict the suitable crops for the given area of land using various parameters such as nutrient content in soil, meteorological parameters and geographical conditions and of the land by using fuzzy logic-based crop diversification system to suggest rural farmers from which farmer can cultivate multiple crops in the same area which can profit them economically. The proposed model has been planned to deal with the ten main crops grown in Andhra Pradesh such as Chili, Cotton, Groundnut, Paddy, Sugarcane, Tobacco, Mango, Millets, Pulses, Wheat. Different fuzzy rule bases were created for every crop to achieve rapid parallel processing. In this proposed model we build the required rules to establish a relationship between the input and output parameters and we established those rules and got desired output using fuzzy logic with a good accuracy.