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PROCHAZKA, D. MAZURA, M. SAMEK, O. POŘÍZKA, P. KLUS, J. NOVOTNÝ, J. KAISER, J.
Original Title
Combination of Laser-Induced Breakdown Spectroscopy and Raman spectroscopy for multivariate classification of bacteria
Type
journal article in Web of Science
Language
English
Original Abstract
In this work, we investigate the impact of data provided by complementary laser-based spectroscopic methods on multivariate classification accuracy. Discrimination and classification of five Staphylococcus bacterial strains and one strain of Escherichia coli is presented. The technique that we used for measurements is a combination of Raman spectroscopy and Laser-Induced Breakdown Spectroscopy (LIBS). Obtained spectroscopic data were then processed using Multivariate Data Analysis algorithms. Principal Components Analysis (PCA) was selected as the most suitable technique for visualization of bacterial strains data. To classify the bacterial strains, we used Neural Networks, namely a supervised version of Kohonen’s self-organizing maps (SOM). We were processing results in three different ways - separately from LIBS measurements, from Raman measurements, and we also merged data from both mentioned methods. The three types of results were then compared. By applying the PCA to Raman spectroscopy data, we observed that two bacterial strains were fully distinguished from the rest of the data set. In the case of LIBS data, three bacterial strains were fully discriminated. Using a combination of data from both methods, we achieved the complete discrimination of all bacterial strains. All the data were classified with a high success rate using SOM algorithm. The most accurate classification was obtained using a combination of data from both techniques. The classification accuracy varied, depending on specific samples and techniques. As for LIBS, the classification accuracy ranged from 45% to 100%, as for Raman Spectroscopy from 50% to 100% and in case of merged data, all samples were classified correctly. Based on the results of the experiments presented in this work, we can assume that the combination of Raman spectroscopy and LIBS significantly enhances discrimination and classification accuracy of bacterial species and strains. The reason is the complementarity in obtained chemical information while using these two methods.
Keywords
Laser-Induced Breakdown Spectroscopy, Raman spectroscopy, chemometrics, bacteria
Authors
PROCHAZKA, D.; MAZURA, M.; SAMEK, O.; POŘÍZKA, P.; KLUS, J.; NOVOTNÝ, J.; KAISER, J.
Released
10. 11. 2017
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Location
THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
ISBN
0584-8547
Periodical
Spectrochimica Acta Part B
Year of study
2018
Number
139
State
United Kingdom of Great Britain and Northern Ireland
Pages from
6
Pages to
12
Pages count
7
URL
https://doi.org/10.1016/j.sab.2017.11.004
BibTex
@article{BUT142311, author="David {Prochazka} and Martin {Mazura} and Ota {Samek} and Pavel {Pořízka} and Jakub {Klus} and Jan {Novotný} and Jozef {Kaiser}", title="Combination of Laser-Induced Breakdown Spectroscopy and Raman spectroscopy for multivariate classification of bacteria", journal="Spectrochimica Acta Part B", year="2017", volume="2018", number="139", pages="6--12", doi="10.1016/j.sab.2017.11.004", issn="0584-8547", url="https://doi.org/10.1016/j.sab.2017.11.004" }