Combination of laser-induced breakdown spectroscopy and Raman spectroscopy for multivariate classification of bacteria

0489532 - ÚPT 2019 RIV NL eng J - Journal Article
Procházka, D. - Mazura, M. - Samek, Ota - Rebrošová, K. - Pořízka, P. - Klus, J. - Procházková, P. - Novotný, J. - Novotný, K. - Kaiser, J.
Combination of laser-induced breakdown spectroscopy and Raman spectroscopy for multivariate classification of bacteria.
Spectrochimica Acta Part B: Atomic Spectroscopy. Roč. 139, JAN (2018), s. 6-12. ISSN 0584-8547. E-ISSN 1873-3565
R&D Projects: GA ČR(CZ) GA15-20645S; GA ČR(CZ) GA16-12477S; GA MŠMT(CZ) LO1212; GA MŠMT ED0017/01/01
Institutional support: RVO:68081731
Keywords : laser-induced breakdown spectroscopy * Raman spectroscopy * chemometrics * bacteria
OECD category: Microbiology
Impact factor: 3.101, year: 2018

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.
Permanent Link: http://hdl.handle.net/11104/0283927