The University of Florida (UF), through its Division of Sponsored Research, was awarded a $420,604.39 Project Grant from the Department of Agriculture's Agriculture and Food Research Initiative (CFDA 10.310) to develop a novel system for fast and reliable detection of spoilage and pathogenic microorganisms in food. The proposed work includes developing a paper chromogenic array enabled by machine learning to detect and quantify the seven most common food pathogens and spoilage microbes across four model food types. The approach aims to provide a fast, low-cost, and versatile method for nondestructive in-field detection of microbial contamination in food. UF is collaborating with the University of Illinois at Urbana-Champaign and the University of Massachusetts Lowell on this project. The University of Illinois is contributing expertise in gas handling, paper array design, and optimization, while the University of Massachusetts Lowell is supporting the development of machine learning pattern recognition algorithms. The award period runs from September 1, 2023 to August 31, 2026.
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