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Integration of Soil Profile Data in Crop Prediction Models: A Comprehensive Review

Tushar Saxena, Dev Verma, Shubham Thapliyal, Tarun Kumar


Farmers in many areas of India are having crop production issues due to soil and climate. There is no comprehensive guide accessible to assist them in developing the appropriate types of plants using modern technology. Farmers may be unable to benefit from agricultural scientific developments due to illiteracy and may continue to rely on human practises. This complicates getting the desired yield. Crop failure, for example, could be the result of fertiliser abuse or unfavourable rainfall patterns. In such situations, the best answer would be to choose crops that are appropriate for the current soil conditions and the anticipated rainfall during planting. As a result, we are launching a 'Soil-Based Profile Profiling System' that is data mining-based. We offer a list of crops that the farmer can grow based on soil input characteristics (NPK and pH) and rainfall in the area. Furthermore, it suggests fertiliser that can be used to enhance soil quality and thus enable more crops to be successfully grown. This desktop application is intended to address the increasing issue of crop failure.


Nitrogen, Phosphorus and Potassium, Artificial Neural Networks, pH, depth, temperature, rainfall, Feedforward backpropagation, Soil.

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