Review - A Machine Learning-Based Fertilizer Recommendation System for Sustainable Crop Yield

Abstract

One of the biggest producers of agricultural goods in the world, India is well known for its textiles, dry fruits, grains, fish, eggs, coconut, sugarcane, and a variety of vegetables. Despite this achievement, large number of Indian farmers continue to cultivate the same crops without considering crop diversification and rotation. Furthermore, overuse of fertilizers, frequently without proper dose understanding, damages long-term production by degrading soil and creating a nitrogen imbalance. We created a machine learning-based recommendation system that makes recommendations for the best crops and fertilizers depending on soil and weather conditions in order to address these problems. This method maximizes productivity while maintaining soil health, allowing for sustainable farming. Through improved crop planning and nutrient management, this approach boosts farmers' profits, promoting environmental sustainability and economic resilience in Indian agriculture.