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Tea Board, ISRO and NIT Rourkela Launch AI Tea Monitoring
India’s Tea Board is working with space and technology experts to watch tea farms.
They will use pictures from satellites and drones.
They will also collect information from farms, weather reports and insect studies.
Computers will help map where tea is grown.
The system may identify plant stress and predict pests and diseases.
It will also estimate how much fresh tea leaf farms can produce.
The project is called CHAAYANKAN and will continue until March 2029.
Officials hope it will make tea farming more productive and sustainable.
Tea Board India signed a tripartite MoU with ISRO’s National Remote Sensing Centre and NIT Rourkela.
The CHAAYANKAN project will run until March 2029 across India’s major tea-growing regions.
The system will combine satellite and UAV imagery with ground, weather and entomological data.
AI tools will map tea areas, detect crop stress, forecast pests and diseases, and estimate green leaf yields.
The project aims to improve tea-sector productivity and sustainability while creating a repository for future policy decisions.
- Who
- Tea Board India, the National Remote Sensing Centre of the Indian Space Research Organisation, and NIT Rourkela.
- What
- They signed a tripartite MoU to develop CHAAYANKAN, an AI-based system for monitoring tea plantations.
- Where
- Across India’s major tea-growing regions.
- When
- The MoU was announced on September 3, 2026; the project is scheduled to run until March 2029.
- Why
- To address crop stress, pest management and yield estimation, while improving productivity, sustainability and technology-driven management.
Key facts
- Project
- CHAAYANKAN — Comprehensive AI-based Geospatial Data Analytics for Tea Plantation Monitoring
- Partners
- Tea Board India, the National Remote Sensing Centre of the Indian Space Research Centre, and NIT Rourkela
- Duration
- Scheduled through March 2029
- Data sources
- Satellite and UAV hyperspectral and optical remote sensing, ground observations, weather inputs and entomological data
- Planned capabilities
- Automatic tea-area mapping, biotic and abiotic stress monitoring, pest and disease forecasting, and green leaf yield estimation
- Expected outcome
- A data repository to support future policy decisions and technology-driven tea-sector management
Sources
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