Document Detail

Identification of meat-associated pathogens via Raman microspectroscopy.
MedLine Citation:
PMID:  24290623     Owner:  NLM     Status:  In-Data-Review    
The development of fast and reliable sensing techniques to detect food-borne microorganisms is a permanent concern in food industry and health care. For this reason, Raman microspectroscopy was applied to rapidly detect pathogens in meat, which could be a promising supplement to currently established methods. In this context, a spectral database of 19 species of the most important harmful and non-pathogenic bacteria associated with meat and poultry was established. To create a meat-like environment the microbial species were prepared on three different agar types. The whole amount of Raman data was taken as a basis to build up a three level classification model by means of support vector machines. Subsequent to a first classifier that differentiates between Raman spectra of Gram-positive and Gram-negative bacteria, two decision knots regarding bacterial genus and species follow. The different steps of the classification model achieved accuracies in the range of 90.6%-99.5%. This database was then challenged with independently prepared test samples. By doing so, beef and poultry samples were spiked with different pathogens associated with food-borne diseases and then identified. The test samples were correctly assigned to their genus and for the most part down to the species-level i.e. a differentiation from closely-related non-pathogenic members was achieved.
Susann Meisel; Stephan Stöckel; Petra Rösch; Jürgen Popp
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Publication Detail:
Type:  Journal Article     Date:  2013-08-22
Journal Detail:
Title:  Food microbiology     Volume:  38     ISSN:  1095-9998     ISO Abbreviation:  Food Microbiol.     Publication Date:  2014 Apr 
Date Detail:
Created Date:  2013-12-02     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8601127     Medline TA:  Food Microbiol     Country:  England    
Other Details:
Languages:  eng     Pagination:  36-43     Citation Subset:  IM    
Copyright Information:
Copyright © 2013 Elsevier Ltd. All rights reserved.
Institute of Physical Chemistry and Abbe Center of Photonics, University of Jena, Helmholtzweg 4, D-07743 Jena, Germany.
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