The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project is enabling food safety testing at most stages in the food-systems value chain by multiple stakeholders, including farmers and consumers at the individual level, the food industry at the points of procurement, storage, and distribution, and by aid agencies to monitor the safety of food aid packages. The initial focus will be to detect two mycotoxins, aflatoxin and fumonisin, both of which are known cancer-causing food contaminants and are found in several food crops including corn. The maximum concentration levels for mycotoxins have been prescribed by many countries; however, these cannot be enforced in most settings because of lack of tools to assess their concentration at the point-of-need. The present work will develop a rapid, low-cost, point-of-need assay for ascertaining food safety with required sensitivity and specificity as recommended by domestic and international food safety agencies. In addition, the team will work with the business partner to optimize the technology for transfer and commercialization to enable it to reach market. It is anticipated that this technology has the potential to significantly reduce unsafe food from the marketplace and improve public health worldwide.

The proposed project is focused on developing a technology for point-of-need assessment of food safety by detection of aflatoxin (AF) and fumonisin (FM) in food crops. These mycotoxins can contaminate several food crops including corn, rice, and peanuts. Consumption of contaminated food can lead to cancer and other adverse health outcomes. The current approach of sending food samples to centralized labs for food safety testing requires expensive equipment, is time-consuming, requires skilled technicians, and is not cost-effective. The proposed technology comprises of a mobile device, a custom-made test strip that accepts food sample extracts and performs the analysis with the help of a smartphone application. The smartphone app operates its imaging system, interprets the test strip results, and displays the results in a few minutes. The analysis results can be transferred to a remote server for monitoring of food safety results. The primary goals of the project include the development of lateral flow assays for AF and FM, optimization of techniques for extracting AF and/or FM from food crops, updating existing smartphone apps to customize them for AF and/or FM detection, and small-scale validation in the lab to determine the performance parameters of the developed sample-in-answer-out assays.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

National Science Foundation (NSF)
Division of Industrial Innovation and Partnerships (IIP)
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Jesus Soriano Molla
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Cornell University
United States
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