CROP YIELD PRIE OPTIMIZER: DYNAMIC MARKET FOREASTING FOR SMALLHOLDER FARMERS

Author(s)	Ms. SHAYINA S, Ms. SIVAKARTHIKA R, Ms. SANGEETHA M, Ms. SOPHIA G
Country	India
Abstract	Smallholder farmers, who produce one-third of the global food supply, are increasingly vulnerable to the dual threats of climate instability and extreme market volatility. Traditional reliance on historical intuition often fails in the face of erratic weather and 'harvest dips'—where localized gluts collapse crop prices. Despite advancements in agritech, small-scale producers frequently lack accessible, integrated tools that link biophysical yield predictions with economic market forecasting. This research introduces the CropYield Price Optimizer, a machine-learning framework designed to bridge this gap by providing real-time, data-driven insights into production outcomes and optimal sale windows.
Keywords	Machine Learning, Crop Yield Prediction, Market Price Forecasting, LSTM, Random Forest, Smallholder Farmers, Precision Agriculture, Rice, Wheat, Maize, Decision Support System.
Field	Biology > Agriculture / Botany
Published In	Volume 7, Issue 2, March-April 2026
Published On	2026-04-29

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