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@article{189667,
        author = {Mr. Alpesh R. Nai and Dr. Jignesh Patel and Mr. Nirav Thakker and Mr. Mahesh Chaudhary and Dr. Namrata Gupta and Dr. Natvar Patel},
        title = {A Machine Learning–Based Crop Recommendation System Using Soil Nutrients and Climatic Factors},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {7},
        pages = {7246-7252},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=189667},
        abstract = {Choosing the right crop is one of the most important decisions in farming, as it directly affects yield, income, and efficient use of resources. Many farmers still rely on experience or traditional practices to select crops, which may not always be suitable under changing soil and climate conditions. This often leads to poor productivity and crop failure. To overcome this problem, this paper presents a machine learning based crop recommendation system that helps farmers select suitable crops based on soil nutrients and climatic factors. The proposed system also focuses on practical usability and clarity of results. By analyzing the influence of individual soil nutrients and climatic factors, the model explains why a particular crop is recommended for given conditions. This helps farmers and agricultural experts understand the decision process rather than relying on predictions alone. Such transparency improves confidence in the system and makes it easier to adopt in real farming scenarios.
The performance evaluation shows that ensemble-based models provide reliable and consistent results across different crops. Accuracy comparisons and visual analyses confirm that the system performs well under varied soil and climate conditions. These findings indicate that the proposed approach can support informed crop planning and reduce uncertainty in agricultural decision-making. Overall, the system offers a practical step toward data-driven and sustainable farming practices.},
        keywords = {Machine Learning, Crop, Soil Nutrients, Climatic Factors, Precision Agriculture, Sustainable Farming.},
        month = {December},
        }