This project aims to improve pest management in greenhouse-grown tomato crops by combining biological control with cutting-edge technology

Federal Project Grant Award Summary

Texas A&M Agrilife Research received a $238,164 Project Grant award from the Department of Agriculture's National Institute of Food and Agriculture (NIFA) under the Crop Protection and Pest Management (CPPM) Competitive Grants Program (CFDA 10.329) on September 30, 2025. The award supports an integrated pest management initiative targeting sweetpotato whitefly (SWF) control in greenhouse-grown tomato crops through the completion date of September 29, 2027. The project delivers three primary products and services: (1) identification and evaluation of natural predator species most effective at reducing SWF populations, including testing of predator combinations to optimize sustainable biological control; (2) development of an automated, artificial intelligence-powered monitoring system using cameras to detect and count SWF in real time, enabling growers to make timely pest management decisions without reliance on chemical pesticides; and (3) extension and outreach activities to promote adoption of these innovations among growers and stakeholders through workshops, farm tours, educational materials, and online platforms.

The project aligns with NIFA's CPPM program objectives to address high-priority pest management challenges through integrated, multifunctional agricultural research and extension activities. By combining biological control research with cutting-edge monitoring technology, the award supports the development of practical, sustainable alternatives to conventional pesticide use while improving crop health in controlled environment agriculture.

Specifically, IT focuses on controlling sweetpotato whitefly (SWF), a major pest in controlled environment agriculture (CEA), using natural predators and an AI-powered monitoring system. Researchers will identify predator species that are most effective at reducing SWF populations and test combinations of these predators to find the best mix for sustainable pest control. At the same time, an automated system will be developed to detect and count SWF in real time using cameras and artificial intelligence, helping growers make timely decisions without relying on chemical pesticides. Extension efforts will ensure that growers and stakeholders learn about and adopt these innovations through workshops, farm tours, educational materials, and online outreach. The overall goal is to reduce pesticide use and improve crop health.