Recommendation of Agricultural Crop Based on Productivity and Season Using Machine Learning

Abstract

Abstract: Many states faces uncertainty in agriculture which decreases its production. With more population and area, more productivity should be achieved but it cannot be reached. Agricultural factors and parameters make the data to get insights about the Agri-facts. Growth of IT world drives some highlights in Agriculture Sciences to help farmers with good agricultural information. The common difficulty present among the Indian farmers are they don’t opt for the proper crop based on their soil necessities. Because of this productivity is affected. This provides a farmer with sort of options of crops which will be cultivated. Agricultural issues like crop prediction, rotation, water requirement, fertilizer requirement and protection can be solved. To implement such an approach, crops are recommended based on its climatic factors and quantity. Data Analytics paves a way to evolve useful extraction from agricultural database. Crop Dataset has been analyzed and recommendation of crops is done based on productivity and season.