Decision Support System to Agronomically Optimize Crop Yield based on Nitrogen and Phosphorus

Abstract

India has always been a high agricultural value country. Agriculture and its industries are one of the country's leading sources of life and economy. The prediction of crops can lead to a positive response that can help farmers improve yields and reduce losses. Natural chemicals like Nitrogen(N), Phosphorus(P), Potassium(K), pH along with soil type (clay soil, black soil, red soil, silt soil, etc.,) and average rainfall dataset are used to predict yield. This project concentrates on balancing macro nutrients (NPK) which is very important requirement for the crop growth. Different doses of these nutrients will be considered foryield prediction of various regions of Karnataka. Since, macro nutrients play major role, by varying the amount of nutrients supplied for crops and sharing this knowledge to farmers will help them to increase crop yield. This proposed work will help farmers to identify the right amount of nutrients supply to particular crops like maize, rice and wheat. Farmers are losing their yield by having lack of knowledge about nutrients requirement for particular crops, this paper concentrates on rice, maize and wheat crop for various regions of Karnataka for prediction. Right quantity of nutrients supply will help farmers to increase their yield.