Artificial Intelligence (AI) is a key tool in accelerating the discovery, development and manufacturing of new crop protection molecules to fight yield-robbing weeds, pests, and diseases in U.S. farm fields.
The technology helps researchers shorten the discovery window and find new and novel active-ingredient molecules that are much more difficult and expensive to uncover using traditional research methods.
That was among the talking points that emerged from Tuesday’s congressional hearing on AI in farming, held in front of the U.S. House of Representatives Science, Space, and Technology Committee in Washington, D.C.
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At the hearing, key agricultural stakeholders advocated for increasing government investment in AI technology and infrastructure. The group warned Congress that America’s status as a world leader in AI has been usurped by Japan and China, while other rival countries are also gunning for top positions.
Testifying on behalf of U.S. agriculture was Corteva Vice President of Agricultural Solutions Brian Lutz, University of Florida associate professor Chris Swale and University of Illinois assistant professor Boris Camiletti.
“AI is without a doubt one of the most profound technologies ever to be invented,” Lutz said. “We believe there is tremendous opportunity for our government to support and incentivize advanced innovation — including by leveraging the benefits of AI — to benefit American farmers. If we want to win, we need to move smarter and faster than our competition. Corteva believes with the support of our government, we will do exactly that.”
Lutz said researchers at Corteva recently used AI to model how 10,000 different molecules might be used in crop protection, all within a matter of weeks. The Corteva model was able to identify dozens of new potential crop protection molecules that its overworked chemists could not have found otherwise. He said the company is currently testing a handful of these molecules and AI will also play a role in moving the testing phase along more quickly than traditional lab-based methods.
Lutz also told Congress how Corteva scientists have deployed AI technology in its fermentation processes, which the company uses to create what he called “molecules of interest” for evaluation. Over the past few years, Corteva has used AI modeling to engineer various bacterial strains that drive fermentation reactions and optimize reaction conditions, allowing the company to run a manufacturing operation that is as efficient as possible. This application of AI helps Corteva maintain a strong U.S. manufacturing base in the Midwest, Lutz said.
“This is the new face of ag innovation,” he added. “We can accelerate discovery of new classes of crop protection products, like biologicals — nature-based solutions that help farmers grow more food by working alongside traditional crop protection products. With AI, we can begin to predict the incredible diversity of biomolecules and metabolites that are produced by microbes and other organisms, with the goal of unlocking the secrets within plant biology to develop the next generation of safe, highly targeted, nature-inspired products.”
Swale testified to AI’s role in helping researchers on his team find and develop biological-based treatments to combat Asian citrus psyllid, an invasive pest that has left the Florida citrus industry — valued at almost $10 billion just five years ago — teetering on the brink of collapse. Effective synthetic chemicals to manage the Asian citrus psyllid exist, but the regulatory hurdles to get those products onto the market are too high, he said
“We have turned to using AI to help discover chemicals of the natural world because the registration requirements are significantly lower when compared to synthetic insecticides,” Swale said.
Camiletti leads a team of researchers combining plant pathology, remote sensing and AI to help U.S. soybean farmers overcome red crown rot, a soil-borne disease first detected in Illinois soybean fields in 2018.
Illinois has been hit the hardest by the yield-robbing disease, Camiletti said, and the pathogen is spreading rapidly to Indiana, Kentucky and Missouri. The disease is difficult to detect visually, he added, and once symptoms appear it’s often too late for successful remediation.
“My team uses satellite imagery and machine learning to identify red crown rot hot spots, and we train the models with high resolution multi-spectral data to near-infrared bands and use ground observations to teach the algorithm what diseased plants look like,” Camiletti said. “This technology has real on-farm impact. We are building tools that generate prescription maps so instead of applying fungicides across entire fields farmers can target only the affected areas.”
After key witness testimony concluded, the committee opened the floor to questions from members of Congress. Watch the full hearing via the video embedded below:
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