CROP AND FERTILIZER RECOMMENDATION SYSTEM USING MACHINE LEARNING

The proposed Crop and Fertilizer Recommendation System effectively assists farmers in selecting suitable crops and fertilizers using machine learning techniques. The system improves agricultural productivity by providing accurate and data-driven recommendations. It reduces dependency on traditional methods and helps in efficient resource utilization. Future enhancements may include integration, real-time weather forecasting systems.

[1] Prediction of crop yield and fertilizer recommendation using machine learning algorithms [2]   Rakesh Kumar, M.P. Singh, Prabhat Kumar and J.P. Singh proposed utilization of seven AI procedures i.e., ANN, Decision Tree, Random Forest, GBDT and Regularized Gradient Forest for crop determination. [3] Machine Learning: Applications in Indian Agriculture, 2018:S. Bhanumathi Et al. [4] Recommender System lecture python notebook by Prof. Junwei Huang [5] Bondre, D. A., et al. “Smart Farming Using Machine Learning and Deep Learning.” IJERT, includes crop yield & fertilizer recommendation. [6] Jitendra, S., & Suneetha, A. “Crop and Fertilizer Recommendation System Using Machine Learning.” IRJMETS, 2023. [7] Ennaji, O., Belgaid, A., & El Allali, A. “Machine Learning-Based Optimization of Site Specific Fertilizer Recommendation.” (ICML Workshop) OpenReview, 2025. [8] Liben, F., Abera, W., Chernet, M. T., Ebrahim, M., Tilaye, A., Erkossa, T., Degefie, T. D., Mponela, P., Kihara, J., & Tamene, L. Pankaj Malik, Dr. “Optimizing Fertilizer Application Using Machine Learning for Precision Agriculture.” IJSET, 2025