AgroPredict: An Explainable AI Framework for Crop and Fertilizer Recommendation using Machine Learning

Agriculture is experiencing rising challenges from inefficiency in resources, climatic variability, and imbalances in soil nutrients, in which traditional approaches are incapable of providing context-based solutions. In an effort to mitigate these limitations, an intelligent decision support system called AgroPredict is suggested. AgroPredict utilizes machine learning and Explainable Artificial Intelligence methods to offer optimized crop selection and fertilizer application recommendations. Naive Bayes is used in crop prediction and Random Forest in fertilizer recommendation to ensure strong and accurate decisionmaking. For enhanced transparency and user trustworthiness, Local Interpretable Model-Agnostic Explanations (LIME) are incorporated in the framework to provide textual and visual interpretations of the predictions of the model. With the combination of predictive accuracy and interpretability, AgroPredict allows farmers to make reliable and data-based agricultural decisions.