Crop Recommendation System

Abstract

Approximately 17% of India's GDP derives from the agricultural sector, which even employs more than 60% of the country's workforce. This field has seen some changes with new technologies like vertical farming and so on. However, many Indian farmers still follow traditional ways and beliefs to use their land. For example, they wait for the weather to match their farming practices, rather than adjusting to the weather changes. Our research goal is to help farmers pick the best crops for their situation and environment by predicting which crops fit well with the factors that influence crop growth, such as soil nutrients, soil pH, humidity and rainfall. We use different machine learning models, such as Decision Tree (DT), Support Vector Machine (SVM), Logistic Regression (LR), and Gaussian Naïve Bayes (GNB).