Title: Laser imaging for rapid Microbial Source Tracking

Authors: Bin Chen, Hao Gong, Xu Zhang, Prithviraj P. Patankar, Michael J. Sadowsky, Charles C. Tseng

Addresses: Department of Electrical and Computer Engineering, Purdue University Calumet, Hammond, IN 46323, USA. ' Department of Electrical and Computer Engineering, Purdue University Calumet, Hammond, IN 46323, USA. ' Department of Biological Sciences, Purdue University Calumet, Hammond, IN 46323, USA. ' Department of Biological Sciences, Purdue University Calumet, Hammond, IN 46323, USA. ' Department of Soil, Water, and Climate, BioTechnology Institute, University of Minnesota, St. Paul, MN 55108, USA. ' Department of Biological Sciences, Purdue University Calumet, Hammond, IN 46323, USA

Abstract: DNA fingerprinting, PCR and other genomic technologies have recently been used to determine sources of fecal bacteria in waterways. Here, we report on the development of a simple and automated optical method for potential use in Microbial Source Tracking (MST) of E. coli. The method employs laser imaging of bacterial colonies and high-resolution optical scattering image analysis for information extraction and classification. Cross validation is used to statistically evaluate the robustness of the classifiers. The entire image analysis procedure can be fully automated, making this a potentially useful tool for future MST studies.

Keywords: laser imaging; MST; microbial source tracking; image decomposition; image classification; E. coli; Escherichia coli; bacterial colonies; optical scattering image analysis; information extraction; information classification; fecal bacteria; waterways; water pollution; water quality.

DOI: 10.1504/IJCBDD.2010.038023

International Journal of Computational Biology and Drug Design, 2010 Vol.3 No.3, pp.177 - 186

Available online: 11 Jan 2011 *

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