Guwahati: Tea Board of India has joined hands with the National Remote Sensing Centre (NRSC) of the Indian Space Research Organisation (ISRO) and NIT Rourkela to develop an AI-powered system for monitoring tea plantations, marking a major push to bring space technology and advanced analytics into India’s tea sector.
A tripartite Memorandum of Understanding (MoU) was signed on August 27, for the three-year research and development project CHAAYANKAN: Comprehensive AI-based Geospatial Data Analytics for Tea Plantation Monitoring.
The project, scheduled to run from April 2026 to March 2029, will cover major tea-growing regions of the country.
At the heart of the initiative is the use of satellite and UAV-based hyperspectral and optical remote sensing, combined with ground observations, weather information and entomological data.
Researchers will use artificial intelligence and machine learning to develop tools capable of detecting changes in tea plantations and predicting threats to crop health.
The project will focus on four key areas: automatic mapping of tea-growing areas, detection of biotic and abiotic stresses, forecasting of major pests and diseases, and estimation of green-leaf yield using satellite and UAV-derived hyperspectral indices.
Tea Board of India will provide technical and field-level support through its existing administrative network, helping researchers integrate ground data with remotely sensed information.
The initiative comes as the tea industry faces persistent challenges linked to crop stress, pest and disease outbreaks and the difficulty of accurately estimating yields.
By combining AI, satellite imagery, drones and field data, CHAAYANKAN is expected to provide tea growers and policymakers with more timely and data-driven information for plantation management.
The project could also create a comprehensive geospatial database of India’s tea plantations, potentially strengthening future planning, research and policy decisions while supporting efforts to improve productivity and sustainability in the sector.
