The University of Hawaiʻi at Mānoa has received a $2 million award from the National Science Foundation (NSF) to lead a multi-institutional effort to develop artificial intelligence (AI)-enabled tools that can help detect environmental threats to food production systems before they become major problems. The effort comes as public health officials continue to investigate foodborne illness outbreaks tied to cyclospora, underscoring the need for faster, more proactive approaches to identifying potential threats in the food supply.
The $4 million NSF Established Program to Stimulate Competitive Research (EPSCoR) Track II Focused EPSCoR Collaboration (FEC) award is led by 糖心视频 Mānoa in partnership with the University of Nebraska–Lincoln. 糖心视频’s portion of the award is $2 million, with the four-year project starting September 1, 2026. This marks only the second time 糖心视频 has received an NSF EPSCoR Track II FEC award.
Team of experts to cross variety of fields
The project will combine AI, environmental sampling, advanced genetic analysis and high-resolution chemical analysis to identify and monitor potential risks to aquaculture, livestock and agricultural systems.
Led by principal investigator Tao Yan, director of the (WRRC) and professor in the , the project brings together researchers from across 糖心视频, including WRRC, College of Engineering, 糖心视频 Cancer Center, School of Ocean and Earth Science and Technology and College of Tropical Agriculture and Human Resilience.
“Food production systems are increasingly challenged by microbial pathogens and chemical contaminants that can threaten animal health, food safety and economic sustainability,” Yan said. “By combining environmental surveillance with AI, we aim to develop early-warning technologies that can identify emerging risks before they reach critical levels. This collaboration will strengthen Hawaiʻi’s and Nebraska’s research capacity while preparing the next generation of scientists and engineers to address complex challenges in food security.”
Creating a proactive approach
Current monitoring methods often identify problems only after disease outbreaks occur or contaminants have reached harmful levels. The project aims to create a proactive approach by continuously analyzing environmental data to detect warning signs earlier.
Researchers will develop new AI models capable of interpreting complex biological and chemical data, including information from metagenomics (the study of genetic material collected from environmental samples) and high-resolution mass spectrometry, which identifies chemical compounds.
The research team will test the technologies in aquaculture and beef cattle production systems, with the goal of improving food safety, protecting animal health and increasing the resilience of food production systems.
The collaboration will support STEM education and workforce development by providing research opportunities for junior faculty members, graduate and undergraduate students, and K–12 participants. Outreach efforts will engage industry partners, regulators and communities to encourage adoption of new technologies.
The partnership builds research capacity in two EPSCoR jurisdictions (Hawaiʻi and Nebraska) while establishing a long-term collaboration focused on using AI and biotechnology to address food system challenges.