Agriculture Marketing and Information System

Agriculture is vital to India's global economy and significantly contributes to GDP. As the human population grows,the nation's agricultural output is crucial in ensuring food security. Climate factors such as temperature, precipitation, soilquality, and fertilizers primarily influence a crop's yield. The variability of these elements adversely impacts productivity,posing a significant challenge for the agriculture industry to accurately estimate crop yields under fluctuating climaticcircumstances. Recently, researchers have used machine learning algorithms to forecast crop yields before actual planting. Thisresearch study has introduced a machine learning technique, namely linear regression and multilayer perception, to forecastcrop production based on characteristics such as state, district, area, seasons, NPK, pH values, rainfall, temperature, and area.To improve yield, this research study recommends a fertilizer tailored to soil conditions, including NPK levels, soil type, pH,humidity, and moisture. Fuzzy algorithms primarily guide the recommendation of fertilizers.