Seasonal Crop Recommendations for High Productivity in India - K Jamunadevi; Dr. K Banuroopa (International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2025)
Tamil Nadu, being a sea-facing state, faces agricultural uncertainty, which diminishes productivity. One can expect higher productivity with a greater number of people and acres of land but cannot do the same. Growers utilize word-of-mouth but are unable to do so with climate conditions. Agricultural factors and terms are utilized. Give information that can be utilized to know more about Agri-facts. Some of the key points in agriculture are motivated by the expansion of the IT world. Sciences to assist farmers with accurate agricultural information. The intelligence of using advanced technological approaches in the agricultural area is optimal in this present situation. Machine Learning techniques create a clear model with the data and enable us to achieve predictions. Agricultural problems such as crop forecasting, rotation, water need, fertilizer need, and protection may be solved. Because of the climatic factors of the environment that vary, a proper method to support crop production, and help farmers improve their production, and management is needed. This would help potential agriculturalists. Better their farming. Using data mining, a farmer can get a system of suggestions to guide them in crop cultivation. Crops are suggested based on climatic factors and how much to use, such as method. Data analytics provides a way to develop useful extraction from agriculture databases. Crop Data set has have been tested, and crop suggestions based on productivity and season have been provided.