Detection of Campylobacter colonies using hyperspectral imaging

The presence of Campylobacter in foods of animal origin is the leading cause of bacterially induced human gastroenteritis. Isolation and detection of Campylobacter in foods via direct plating involves lengthy laboratory procedures including enrichments and microaerobic incubations, which take several days to a week. The incubation time for growing Campylobacter colonies in agar media usually takes 24–48 h. Oftentimes the problem is the difficulty of visually differentiating Campylobacter colonies from non-Campylobacter contaminants that frequently grow together with Campylobacter on many existing agars. In this study, a new screening technique using non-destructive and non-contact hyperspectral imaging was developed to detect Campylobacter colonies in Petri dishes. A reflectance spectral library of Campylobacter and non-Campylobacter contaminants was constructed for characterization of absorption features in wavelengths from 400 to 900 nm and for developing classification methods. Blood agar and Campy-Cefex agar were used as culture media. The study found that blood agar was the better culture medium than Campy-Cefex agar in terms of Campylobacter detection accuracy. Classification algorithms including single-band thresholding, band-ratio thresholding and spectral feature fitting were developed for detection of Campylobacter colonies as early as 24 h of incubation time. A band ratio algorithm using two bands at 426 and 458 nm chosen from continuum-removed spectra of the blood agar bacterial cultures achieved 97–99% of detection accuracy. This research has profound implications for early detection of Campylobacter colonies with high accuracy. Also, the developed hyperspectral reflectance imaging protocol is applicable to other pathogen detection studies.

[1]  C. Gables,et al.  Analytical utility of Campylobacter methodologies. , 2007, Journal of food protection.

[2]  J. Line,et al.  Development of a selective differential agar for isolation and enumeration of Campylobacter spp. , 2001, Journal of food protection.

[3]  K. Lawrence,et al.  Hyperspectral Reflectance Imaging for Detecting a Foodborne Pathogen: Campylobacter , 2009 .

[4]  Robert A. Meyers,et al.  Encyclopedia of analytical chemistry : applications, theory and instrumentation , 2000 .

[5]  W. R. Windham,et al.  CALIBRATION OF A PUSHBROOM HYPERSPECTRAL IMAGING SYSTEM FOR AGRICULTURAL INSPECTION , 2003 .

[6]  U. Lyhs,et al.  Campylobacter in the food supply , 2008 .

[7]  Grahame W. Gould,et al.  Microbiological Safety and Quality of Food , 1999 .

[8]  Paul M. Mather,et al.  Computer Processing of Remotely-Sensed Images: An Introduction , 1988 .

[9]  R. Clark,et al.  Reflectance spectroscopy: Quantitative analysis techniques for remote sensing applications , 1984 .

[10]  D. Mouwen,et al.  Discrimination of Enterobacterial Repetitive Intergenic Consensus PCR Types of Campylobacter coli and Campylobacter jejuni by Fourier Transform Infrared Spectroscopy , 2005, Applied and Environmental Microbiology.

[11]  F. Kruse Use of airborne imaging spectrometer data to map minerals associated with hydrothermally altered rocks in the northern grapevine mountains, Nevada, and California , 1988 .

[12]  W. Press,et al.  Numerical Recipes in C++: The Art of Scientific Computing (2nd edn)1 Numerical Recipes Example Book (C++) (2nd edn)2 Numerical Recipes Multi-Language Code CD ROM with LINUX or UNIX Single-Screen License Revised Version3 , 2003 .

[13]  William H. Press,et al.  Numerical recipes in C. The art of scientific computing , 1987 .

[14]  M. Speck Compendium of methods for the microbiological examination of foods , 1976 .

[15]  Haibo Yao,et al.  Differentiation of toxigenic fungi using hyperspectral imagery , 2008 .

[16]  G. Siragusa,et al.  Serological methods and selective agars to enumerate Campylobacter from broiler carcasses: data from inter- and intralaboratory analyses. , 2004, Journal of food protection.

[17]  C. Vanderzant,et al.  Compendium of Methods for the Microbiological Examination of Foods , 1992 .

[18]  R. Clark,et al.  Spectroscopic Determination of Leaf Biochemistry Using Band-Depth Analysis of Absorption Features and Stepwise Multiple Linear Regression , 1999 .

[19]  Ray Bert,et al.  Book Review: Computer Processing of Remotely-Sensed Images: An Introduction, Third Edition , by Paul M. Mather. Chichester, United Kingdom: John Wiley & Sons Ltd., 2004 , 2004 .