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UF/IFAS researcher says robotics, AI could reduce pesticide use and ease labor shortages
Summary
Dr. Nathan Boyd (UF/IFAS Gulf Coast Research & Education Center) told the committee that targeted-spray and harvesting robots can cut inputs, reduce pesticide and fungicide use (he cited a >50% reduction for some targeted-spray cases), and help address farm labor shortages while offering benefits to small and large growers.
Dr. Nathan Boyd of the UF/IFAS Gulf Coast Research and Education Center told the Senate Agriculture Committee that recent advances in open-source software, robotic platforms and machine learning are expanding targeted-spray, disease detection and harvesting technologies. "This type of practice drops fungicide use by over 50% across the season," he said, describing a watermelon-targeted-spray program from his lab as an example.
Boyd described technologies that detect crops and disease in two- and three-dimensional imagery, map trees for citrus management (citing commercial tools such as AgriView), and allow small units or fleets (for example, Greenfield Robotics) to serve both small and large growers. He said autonomous tractors and harvesting prototypes (he mentioned Crew Robotics' strawberry-harvesting work) are becoming more available and that these systems can increase efficiency, reduce pesticide residues and lower input costs.
Addressing labor pressures, Boyd said automation is driven by aging farm operators and a small domestic agricultural labor pool; he cited industry estimates that robotics and AI will raise agricultural production substantially and listed growth estimates for related markets. He also noted Florida initiatives, including a new center for applied artificial intelligence in agriculture and private-sector investment in ag tech. Committee members did not pursue detailed questioning during this presentation.
