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Precision Agriculture Research

Precision farming intelligence for South Asian crops. Climate modeling for the agricultural systems that feed 2 billion people.

Current focus areas

  • Crop yield optimization models for rice, tea, and coconut using DOA historical yield data and 20-year monsoon patterns.
  • Satellite-based crop stress detection from Sentinel-2 and Landsat-9 multispectral imagery (NDVI and derivatives).
  • Climate impact forecasting for South Asian monsoon agriculture.
  • AI-assisted irrigation scheduling integrating soil-sensor data with short-range weather forecasts.

Phase 01 active. First live pilot deployment: within 6 months of launch.

Partnership

Official partnership with the Sri Lanka Department of Agriculture.

First live pilot deployment: within 6 months of site launch.

Live from the frontier

Recent research

Questions

Precision Agriculture Research — questions

What crops does the agriculture lab focus on?

The Advanced Agriculture laboratory focuses initially on rice, tea, and coconut — Sri Lanka's primary agricultural exports and food crops. The first live pilot is a rice-yield prediction model for the North Central Province, the country's main paddy-growing region.

Is ASI Research Lab partnered with the Sri Lanka Department of Agriculture?

Yes. The partnership with the Sri Lanka Department of Agriculture is an active data-sharing relationship. DOA provides historical yield data, soil classification maps, and field-trial data; ASI Research Lab provides research outputs the DOA can deploy through its extension services.

How does satellite crop-stress detection work?

Sri Lanka's agricultural land is covered by the free Sentinel-2 (ESA) and Landsat-9 (NASA) programs. NDVI and derivative indices from this multispectral imagery provide reliable early indicators of crop stress, converted into field-level alerts through an automated processing pipeline.

When does the first agriculture deployment happen?

The first live pilot deployment is targeted within six months of site launch: a rice-yield prediction model for the North Central Province. The scope is deliberately narrow, specific, and achievable.