Google DeepMind Partnered With ICRISAT for Sorghum AI
The open-source platform aims to accelerate breeding of drought-resistant crops for 500 million people.
Updated on Oct. 12, 2026 in Artificial Intelligence
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Google DeepMind and the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) have launched an open-source AI platform to advance research on sorghum, commonly known as jowar. This research-stage initiative aims to shorten breeding cycles that traditionally span a decade or more.
Why it matters
Jowar is currently categorized as an orphan crop, receiving significantly less scientific investment than major global staples despite its importance to food security. By applying machine learning to crop genetics, the project attempts to mitigate production losses from drought and disease.
The initiative leverages AI tools to compress breeding timelines that historically require ten or more years of development. The platform is designed to build local research capacity to support the 600,000 farmers currently participating in the related AnthroKrishi program.
The players
Google DeepMind
A research laboratory focused on artificial general intelligence and machine learning applications in scientific discovery.
ICRISAT
An international research organization focused on agricultural development in semi-arid regions of Asia and Africa.
The details
Researchers integrate stakeholder input from the AnthroKrishi initiative, which works with 600,000 farmers, directly into the platform's development process. The system utilizes machine learning to identify genetic markers for drought and disease resistance, replacing slower, traditional selection methods. This approach is intended to modernize the cultivation of jowar, an orphan crop — a plant that is culturally and economically important but has historically lacked significant scientific investment.
Timeline
Historically, jowar has been categorized as an orphan crop due to limited research investment.
The Tech Race
This project scales the existing AnthroKrishi initiative, which currently operates across 11 countries, by adding a technical layer for genetic research. It marks a shift from community-based outreach to data-driven crop engineering for crops neglected by global agricultural research programs.
Farmers across 11 countries in India and Africa may gain access to more resilient crop varieties as these research-stage tools enter field application. The project prioritizes local capacity building, allowing regional researchers to utilize these AI tools for future breeding cycles.
The takeaway
The project serves as a test case for whether AI can elevate orphan crops to the same research velocity as global staples. Watch for future benchmarks regarding the timeline reduction in successful breeding of drought-resistant sorghum varieties.
Further reading
Explore recent developments in agricultural machine learning on our Artificial Intelligence page.
Source note: This article includes information reported by NDTV Profit.
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