BACTERIAL PATTERN IDENTIFICATION IN NEAR-INFRARED SPECTRUM

Pavel Krepelka

xkrepe01@stud.feec.vutbr.cz
Brno University of Technology, Department of Theoretical and Experimental Electrical Engineering (Czechia)

Fernando Pérez-Rodríguez


Universidad de Córdoba, Departamento de Bromatología y Tecnología de los Alimentos (Spain)

Karel Bartusek


Academy of Sciences of the Czech Republic, Institute of Scientific Instruments (Czechia)

Abstract

Microorganism identification, primary bacterial identification and pathogen detection, is important in a lot of microbial scientific areas (diagnosing of infection diseases, food protection). In this paper, the identification of the strains was performed by Near Infrared spectroscopy (wavelength from 900 nm to 2500 nm). Different techniques for classification (CVA, ANN…) were examined. It was reached to 100% accuracy on limited count of samples. Because a removing of water from sample represents a time-consuming step in sample preparation process, influence of water to spectrum was examined.  Near Infrared (NIR) spectroscopy seems to be a suitable method for rapid bacteria identification. It can be used in a wide variety of food protection, medicine microbiology, bio-terrorism threats and environmental studies.


Keywords:

infrared imaging, spectroscopy, cells, absorption, near infrared spectroscopy

Alexandrakis D., Downey G., Scannell A. G. M.: Detection and identification of bacteria in an isolated system with near-infrared spectroscopy and multivariate analysis, Journal of agricultural and food chemistry, Vol. 56 (10), pp. 3431-3437.
  Google Scholar

Burns, D.A., Ciurczak, E.W.: Handbook of near-infrared analysis, Third Edition, CRC Press, 2008.
  Google Scholar

Cámara-Martos F., Zurera-Cosano G., Moreno-Rojas R., García-Gimeno R.M., Pérez-Rodríguez F.: Identification and Quantification of Lactic Acid Bacteria in a Water-Based Matrix with Near-Infrared Spectroscopy and Multivariate Regression Modeling, Food Analytical Methods, Vol. 5 (1), pp. 19-28.
  Google Scholar

Krepelka, P.: Identification of bacteria strains via advanced methods for the statistical processing of near- infrared spectra, Proceedings of PIERS 2013, Stockholm, 2013.
  Google Scholar

Naes T., Isakson T., Fearn T., Davies. T.: A user-friendly guide to multivariate calibration and classification, NIR Publications, Chichester, 2003, DOI: 10.1002/cem.815
  Google Scholar

Rodriguez-Saona L.E., Khambaty F.M., Fry F.S., Calvey E.M.: Rapid detection and identification of bacterial strains by Fourier transform near-infrared spectroscopy. J Agric Food Chem. 2001, Vol 49(2), pp. 574-9.
  Google Scholar

Siesler H. W., Ozaki Y., Kawata S., Heise H. M.: Near-infrared spectroscopy. Principles, instruments, applications, Wiley-VCH, Weinheim, 2002.
  Google Scholar

Stuard, B.: Infrared spectroscopy: fundamentals and application, Ants wiley, 2004.
  Google Scholar

Thennadil S. N., Martens H., Kohler A.: Physics-Based Multiplicative Scatter Correction Approaches for Improving the Performance of Calibration Models, Appl. Spectrosc., 2006, Vol. 60, pp. 315-321.
  Google Scholar

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Published
2014-09-26

Cited by

Krepelka, P., Pérez-Rodríguez, F., & Bartusek, K. (2014). BACTERIAL PATTERN IDENTIFICATION IN NEAR-INFRARED SPECTRUM. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 4(3), 58–60. https://doi.org/10.5604/20830157.1121369

Authors

Pavel Krepelka 
xkrepe01@stud.feec.vutbr.cz
Brno University of Technology, Department of Theoretical and Experimental Electrical Engineering Czechia

Authors

Fernando Pérez-Rodríguez 

Universidad de Córdoba, Departamento de Bromatología y Tecnología de los Alimentos Spain

Authors

Karel Bartusek 

Academy of Sciences of the Czech Republic, Institute of Scientific Instruments Czechia

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