Sustainable Fertilizers in Coffee Plantation: Hybrid Recommendation for Agricultural Producers
S Raveena, R Surendran
Abstract
To improve soil fertility and crop yields, early agricultural practices include the use of natural materials such as animal dung, compost, and crop wastes. They apply fertilizers at random not realizing the deficient type or amount. As a result, crop yield is immediately affected, as well as soil acidification and harm to the uppermost stratum. The hybrid recommendation system with a machine learning strategy was applied in the proposed framework. In contrast to numerous algorithms for estimating and evaluating historical yield concerning nutrient parameters. Farmers can use an interactive web source to post concerns to get a prompt reply with accurate fertilizer recommendations. Beyond that, extensive testing on real-world datasets obtained 92.5% accuracy, demonstrating the usefulness and efficiency of the proposed methodology.