Market Driven Crop Price Prediction

Abstract

The global agricultural sector faces significant challenges in ensuring food security, optimizing resource utilization, and adapting to changing environmental conditions. Accurate crop price prediction is crucial for addressing these challenges, yet existing methodologies often lack the ability to integrate market dynamics effectively. This paper proposes a novel framework for market- driven crop price prediction, leveraging advanced machine learning techniques and market data integration to enhance the accuracy and relevance of predictions. The crop price predictor can be applied to minimize losses when adverse situations occur. Farmers can use this system to maximize crop yield rates when the potential exists for favorable growing conditions