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@article{177673,
        author = {Mrs.Samundeeswari.K and Dr.Aysha Banu.B and M.Harini Priya and S.S.Deepika and A.Srikavi},
        title = {AGRICULTURAL CROP RECOMMENDATIONS BASED ON PRODUCTIVITY AND SEASON},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {2698-2702},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=177673},
        abstract = {As a coastal state, Tamil Nadu faces agricultural uncertainty due to climatic factors, limiting productivity despite its large population and area. Traditional word-of-mouth practices are no longer effective. Agricultural parameters generate data that can offer valuable insights. The growth of IT has impacted Agricultural Sciences, aiding farmers with better information. Modern technological methods, especially Machine Learning, are essential today. These techniques build models to predict and address issues like crop prediction, rotation, water and fertilizer needs, and crop protection. Due to changing climate, efficient techniques are needed to support cultivation and assist farmers. This can benefit future agriculturalists. A recommendation system, using data mining, can guide farmers in crop cultivation based on climatic factors and quantity. Data Analytics enables effective extraction from agricultural databases, and crop datasets are analyzed to recommend crops based on productivity and season.},
        keywords = {},
        month = {May},
        }