• Mrs G Ramajayam
• Priya A S
• P Vasanthi Rohini

Tamil Nadu, a coastal state facing agricultural challenge due to unpredictable climate, can benefit from integrating machine learning and data mining techniques to enhance farming practices. Traditional methods of knowledge sharing are increasingly unreliable, making it essential to adopt modern technologies for better crop management. Machine learning models can provide accurate predictions on crop selection, water and fertilizer needs, and protection strategies. By leveraging data analytics, farmers can receive tailored recommendations that improve productivity and sustainability, helping them make informed decisions based on real-time climatic and environmental data, thereby supporting sustainable farming practices.

Machine Learning, Light GBM, Crop and Yield Prediction, Data Mining, Agricultural Analytics.

"AGRICULTURAL CROP RECOMMENDATIONS BASED ON PRODUCTIVITY AND SEASON ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 2, page no.g467-g470, February-2025, Available :http://www.jetir.org/papers/JETIR2502654.pdf

"AGRICULTURAL CROP RECOMMENDATIONS BASED ON PRODUCTIVITY AND SEASON ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 2, page no. ppg467-g470, February-2025, Available at : http://www.jetir.org/papers/JETIR2502654.pdf