Crop Prediction System Using Machine Learning

Abstract

This research focuses on a Crop Prediction System designed to assist farmers and agricultural professionals in selecting the most suitable crop based on soil and climatic parameters. By leveraging machine learning algorithms, the system analyzes environmental data such as soil nutrients (NPK values), pH, temperature, humidity, and rainfall to recommend optimal crops for cultivation. Implemented using Python and Flask, the system provides a user-friendly web interface for real-time predictions. This study demonstrates how AI and data analytics can revolutionize agriculture by enhancing crop yield, resource efficiency, and sustainable farming practices.