A Machine Learning model for Crop and Fertilizer recommendation

Abstract

India is currently the world's second largest producer of several dry fruits, agriculture-based textile raw materials, roots and tuber crops, pulses, farmed fish, eggs, coconut, sugarcane and numerous vegetables. India is ranked under the world's five largest producers of over 80% of agricultural produce items, including many cash crops such as coffee and cotton. Farmers are growing same crop in the season rather than growing different varieties in various seasons, also applying more quantity of fertilizers without knowing actual contents and quantity. So we have designed a recommendation model based on machine learning , describes the best suitable crop to be grown and fertilizer to be seeded depending on soil and weather conditions. Hence by utilizing our system,farmers can grow new crops in different seasons and benefit a better profit, avoid soil pollution.