Abstract

Tamil Nadu, as a coastal state, faces significant agricultural challenges due to climate variability, leading to reduced production despite its large population and extensive farming area. Traditional word-of-mouth practices are no longer effective, necessitating the adoption of modern technological methods. The integration of data analytics and machine learning in Agricultural Sciences offers valuable insights and predictive models to address issues such as crop prediction, rotation, water and fertilizer requirements, and pest protection. By analyzing climatic factors and crop data, a recommendation system can guide farmers in crop cultivation, enhancing productivity and supporting better management practices. This approach not only aids current farmers but also equips future agriculturalists with the knowledge to achieve improved agricultural outcomes.