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Field NotesDecember 04, 20257 min read

From satellite pixels to sowing decisions

How a weather forecast, a soil map and a crop model come together into one timely recommendation.

A sowing decision looks simple: plant now, or wait. But getting it right means combining rainfall onset forecasts, soil moisture state, variety-specific phenology and risk tolerance — and delivering the result before the window closes.

The ingredients

Our advisory pipeline fuses three layers. Satellite and in-situ sensing estimate soil moisture and field readiness. Downscaled weather models predict onset and early-season rainfall. A crop model then runs the scenarios: what does this variety need, and what is the risk profile of each sowing window?

The output is a decision, not a map

Farmers do not need more data — they need better decisions. Our output is a recommendation with a confidence level and an alternative: 'Sowing window opens 22 June with moderate risk; waiting 6 days improves emergence odds by 11%.' That sentence carries more value than a hundred maps.

What the field taught us

Early pilots taught us that trust in the recommendation depends on the alternative being explicit, and on the model admitting uncertainty. Farmers already manage risk daily; our job is to make the trade-offs legible.

Written by the Somadhan Research Team

Somadhan Technologies is a research-first AI startup building cutting-edge solutions for agriculture.