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The aim is to create a system that predicts crop prices and aids farmers in decision-making.

May 7, 2026Iconic Research and Engineering Journals

Agriculture Crop Price Forecasting and Advisory System

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The aim is to create a system that predicts crop prices and aids farmers in decision-making.
Utilized machine learning and data analytics to analyze historical agricultural data.
Employed a Linear Regression model to forecast future crop prices and evaluated performance with statistical measures.
Developed an interactive dashboard using Power BI for effective visualization of insights and trends.
The system provided reliable predictions with a significant reduction in Mean Squared Error.
R-squared score indicated a strong correlation between forecasted and actual crop prices.
Farmers reported improved profitability and reduced risk through data-driven decision-making.

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Randomized trial demonstrates effective crop price predictions in agriculture, suggesting improved decision-making for farmers.

Reddy et al. (2026) studied this question.

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