Crop Recommendation System Using Machine Learning

Given that it accounts for 17% of the nation’s GDP and employs more than 60% of the workforce, agriculture is one of India’s largest and most diverse economic sectors. Numerous biotic along with abiotic parameters are used to make crop suggestions to boost agricultural productivity. It helps keep food prices down and favors farmers and the entire nation. Indian farmers frequently struggle with the issue of improper crop choice concerning the needs of their land. As a result, their output has been severely hindered. So, the crop recommendation model in this chapter thus uses research-based data on soil characteristics and soil classifications for farms to select the appropriate according to site-specific crop factors. By analyzing the datasets and applying machine-learning classifiers, including Decision Tree, Logistic Regression, and Random Forest, this model calculates the optimal crop for each soil type. As a result, choosing the right crop is easier, increasing productivity.