New challenge aims to speed crop innovation using advanced data tools
The U.S. Department of Agriculture (USDA) is preparing a new initiative that aims to accelerate crop innovation through artificial intelligence.
Working through the Genesis Mission and the Agriculture Advanced Research and Development Authority (AgARDA), USDA plans to launch an Agricultural National Science & Technology Challenge later this year. The effort will encourage innovators, researchers, universities, and technology experts to develop AI-powered tools that can make better use of large amounts of plant data.
The challenge will focus on combining different types of information, including images, field observations, and laboratory results. By bringing these data sources together, scientists will be able to identify valuable plant and seed traits more quickly and accurately. This could help speed the development of crops that are more productive, resilient, and better suited to future agricultural needs.
According to USDA, modern AI technologies can help researchers unlock important insights from extensive germplasm collections. Germplasm contains genetic material used in plant breeding and crop improvement programs. Making this information easier to analyze could lead to faster scientific discoveries and stronger food production systems.
“USDA is taking concrete steps to give scientists the modern tools they need to innovate agricultural solutions from the vast plant data that they collect,” said REE Under Secretary and USDA Chief Scientist Dr. Scott Hutchins. “When our partners help us to solve agricultural challenges by using AI tools, we’ll unlock faster discoveries with germplasm data and grow better crops that strengthen our food system for many future generations.”
The initiative is connected to the Genesis Mission, a national program launched in 2025 and coordinated by the White House Office of Science and Technology Policy. The mission encourages collaboration among scientists, businesses, universities, data repositories, and government organizations to solve complex scientific challenges using AI.
Teams participating in the challenge are expected to gain access to shared resources and infrastructure that connect scientific datasets, research equipment, and AI technologies. Additional details about the competition are expected to be released in the coming months.
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