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Updated: Jan 30, 2026

Combining Raman Imaging and Multivariate Analysis to Visualize Lignin, Cellulose, and Hemicellulose in the Plant Cell Wall
Published on: June 10, 2017
Detection of spoilage associated bacteria using Raman-microspectroscopy combined with multivariate statistical
Daniel Klein1, René Breuch1, Sune von der Mark1
1Bonn-Rhein-Sieg University of Applied Sciences, Institute of Safety and Security Research, von Liebig-Straße 20, 53359 Rheinbach, Germany.
Abstract:
Raman-Microspectroscopy with subsequent chemometric evaluation was used for the rapid and non-destructive differentiation of seven important spoilage related microorganisms, namely Brochothrix thermosphacta DSM 20171, Pseudomonas fluorescens DSM 4358, Pseudomonas fluorescens DSM 50090, Micrococcus luteus, Escherichia coli HB101, Escherichia coli TOP10 and Bacillus thuringiensis israelensis DSM 5724. Therefore fast collected spectra directly from rapid surface blots without any pretreatments like purification or singulation steps were used. To estimate and classify the Raman-spectroscopic data at genera and strain level an adequate preprocessing together with a subsequent chemometric evaluation consisting of principal component analysis and discriminant analysis was used. Thereby, importance was attached to a balanced data set, as this makes the multivariate analysis of the data significantly more resilient and meaningful. The analysis showed that the differentiation of spoilage related microorganisms on genera and strain level was successful and the classification of independent test data showed only an error rate of 3.5%.
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