Agriculture Portal: ML & API Solutions for Farmers

ABSTRACTAgriculture is highly dependent on soil conditions,climatic factors, and timely decision-making. Traditionalfarming practices rely on experience-based judgments,which often lead to inefficient crop selection, improperfertilizer usage, and yield uncertainty. This paper presentsan Agriculture Portal integrated with MachineLearning (ML) and API-based services to assist farmersin making data-driven decisions. The proposed systemprovides crop prediction, fertilizer recommendation,yield estimation, rainfall forecasting, real-time weatherupdates, agricultural news, and AI-based farmerassistance through a unified web platform. Machinelearning models are trained using historical agriculturaland environmental data to generate accurate predictions.External APIs are integrated to deliver real-time weatherinformation and agriculture-related updates. The resultsdemonstrate that the system improves farming efficiency,reduces manual analysis, minimizes risk, and supportssustainable agricultural practices.