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4 October 2020 Detecting foodborne pathogens with darkfield hyperspectral microscopy
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Abstract
The presence of pathogenic microorganisms such as salmonella, listeria and E. coli in foods is a major threat to consumer safety. The failure to detect these pathogens can result in severe outbreaks of foodborne illness. There are several technologies utilized in food pathogen detection today including plating, nucleic acid-based polymerase chain reaction techniques and immunoassays. While these technologies have their merits, each approach requires significant sample incubation and total time to answer of 18 – 72hrs. HinaLea is working in collaboration with the USDA to develop a system which will significantly accelerate the identification of foodborne pathogens. The system combines darkfield microscopy, hyperspectral imaging, machine learning and automation in a standalone unit. Our vision is to move towards real-time identification of pathogens in the food production environment.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alexandre Fong, George Shu, Barry McDonogh, and Bosoon Park "Detecting foodborne pathogens with darkfield hyperspectral microscopy", Proc. SPIE 11576, Hyperspectral Imaging and Applications, 115760C (4 October 2020); https://doi.org/10.1117/12.2584913
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