Paper
10 February 1995 Ultraviolet fluorescence identification of protein, DNA, and bacteria
Philip J. Hargis Jr., T. J. Sobering, Gary C. Tisone, John S. Wagner, Steve A. Young, R. J. Radloff
Author Affiliations +
Proceedings Volume 2366, Optical Instrumentation for Gas Emissions Monitoring and Atmospheric Measurements; (1995) https://doi.org/10.1117/12.205554
Event: Optical Sensing for Environmental and Process Monitoring, 1994, McLean, VA, United States
Abstract
Recent food poisoning incidents have highlighted the need for inexpensive instrumentation that can detect food pathogens. Instrumentation that detects the relatively strong ultraviolet (UV) fluorescence signal from the aromatic protein amino acids in bacteria could provide a solution to the problem of real-time pathogen measurements. The capabilities of UV fluorescence measurements have, however, been largely ignored because of the difficulty in identifying pathogens in the presence of interfering backgrounds. Implementation of fluorescence measurements thus requires methodologies that can distinguish fluorescence features associated with pathogens from those associated with proteins, harmless bacteria, skin, blood, hair follicles, pesticide residue, etc. We describe multispectral UV fluorescence measurements that demonstrate the feasibility of detecting and identifying protein, DNA, and bacteria using a relatively simple UV imaging fluorometer and a unique multivariate analysis algorithm.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Philip J. Hargis Jr., T. J. Sobering, Gary C. Tisone, John S. Wagner, Steve A. Young, and R. J. Radloff "Ultraviolet fluorescence identification of protein, DNA, and bacteria", Proc. SPIE 2366, Optical Instrumentation for Gas Emissions Monitoring and Atmospheric Measurements, (10 February 1995); https://doi.org/10.1117/12.205554
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Cited by 15 scholarly publications.
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KEYWORDS
Luminescence

Ultraviolet radiation

Pathogens

Bacteria

Proteins

Algorithm development

Detection and tracking algorithms

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