Research

Agricultural Sciences

Title :

Empowering Farmers with Machine Learning-Based Price Forecasts for Plantation Crops of West Coast of India

Area of research :

Agricultural Sciences

Focus area :

Quantitative Social Sciences

Principal Investigator :

Dr. Shripad Bhat, ICAR - Central Coastal Agricultural Research Institute,Goa

Timeline Start Year :

2024

Timeline End Year :

2027

Contact info :

Details

Executive Summary :

This project aims to develop forecasting models for price analysis of important plantation crops in the west coast of India, such as black pepper, cashew, arecanut, and coconut. These crops support the livelihoods of lakhs of farm families in the region. Price fluctuations affect farm income and increase the risk faced by farmers. Farmers can store these crops for up to six months before selling in the market. Timely price forecasts and market intelligence reports enable farmers to make informed marketing decisions, such as whether to store or sell produce. Data on prices of these crops will be collected from major markets in the west coast of India using open-source software and models like AutoRegressive Integrated Moving Average (ARIMA), Seasonal AutoRegressive Integrated Moving Average (SARIMA), Long Short-Term Memory Networks (LSTM), and Gated Recurrent Unit (GRU). Price-forecasts-based market intelligence reports will be disseminated to farmers through social media and institute websites. The expected outcomes are the identification of the best-performing model for price forecasts and enhanced income for farmers.

Total Budget (INR):

6,60,000

Organizations involved