Detail publikace

Combination of Laser-Induced Breakdown Spectroscopy and Raman spectroscopy for multivariate classification of bacteria

PROCHAZKA, D. MAZURA, M. SAMEK, O. POŘÍZKA, P. KLUS, J. NOVOTNÝ, J. KAISER, J.

Originální název

Combination of Laser-Induced Breakdown Spectroscopy and Raman spectroscopy for multivariate classification of bacteria

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

Laser-Induced Breakdown Spectroscopy, Raman spectroscopy, chemometrics, bacteria

Autoři

PROCHAZKA, D.; MAZURA, M.; SAMEK, O.; POŘÍZKA, P.; KLUS, J.; NOVOTNÝ, J.; KAISER, J.

Vydáno

10. 11. 2017

Nakladatel

PERGAMON-ELSEVIER SCIENCE LTD

Místo

THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND

ISSN

0584-8547

Periodikum

Spectrochimica Acta Part B

Ročník

2018

Číslo

139

Stát

Spojené království Velké Británie a Severního Irska

Strany od

6

Strany do

12

Strany počet

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"
}