Abstract
Abstract: The Crop Recommendation System proposes a mixed model to suggest crops for Indian states, considering various factors such as soil pH, moisture, NPK levels, crop data, and temperature. This suggestion model is constructed as a sample model incorporating supervised machine learning algorithms. The technology- based agricultural crop identifier model aims to enhance farmers crop yield by identifying appropriate crops based on their parameters. The efficacy of the recommendation model lies in its ability to recommend the right crop for specific conditions, which in turn contributes to addressing agricultural and farming challenges and boosting the Indian economy by maximizing crop production. The system also includes a grading process to identify crop quality and signalling the presence of low and high-quality crops. The utilization of a set of classifiers facilitates improved decision-making through multiple classifiers. The assessment process includes a request for decisionmaking to determine the outcomes of the classifiers
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