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@article{180696,
        author = {Himanshu bhushan and Charan N P and Dayakar reddy K and Dr. Sandhya G},
        title = {Soil Analysis and Crop Recommendation using Machine Lerning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {2918-2923},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180696},
        abstract = {Agriculture is the backbone of Indian economy and livelihood to many people. Farmers often choose crops for their field based on their own experience and instinct. This sometimes leads to loss and less yield. If the selection of crop is done with the productivity data of the entire region, it may lead to better results. However, all the crops cannot be cultivated in a particular soil. So, the soil must be analysed crops must be suggested based on the type of soil. This work suggests an idea that is useful and eaisly accesible to all farmers of India without any need of hardware. A list of crops with their success rate will be suggested to the farmer when the region of agriculture and soil image are given as inputs. This list of crops is both profitable and produce more yield in that region.},
        keywords = {CNN (Convolution Neural Network), soil pH, sustinable agriculture, crop prediction.},
        month = {June},
        }