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Issue 10 (3) 2011 pp. 275-285

Bartłomiej Dziuba

University of Warmia and Mazury in Olsztyn

Identification of selected Leuconostoc species with the use of FTIR spectroscopy and artificial neural networks

Abstract

 

Background. FTIR spectroscopy is becoming an important tool in the differentiation and identification of bacteria. In the present study, lactic acid bacteria of the genus Leuconostoc were differentiated and identified with the use of Fourier transform infrared spectroscopy (FTIR) and artificial neural networks (ANNs). The aim of the study was to expand the existing library of FTIR spectra of lactic acid and propionic acid bacteria, and to develop multilayer artificial neural networks as part of the same structure.
Material and methods. The material for this study were 10 reference strains of the genus Leuconostoc, and 24 strains isolated from food products. The isolated pure cultures were identified with species specific pairs of primers by PCR technique, as a reference method. Bacterial strain samples were subjected to spectroscopic measurements by the transmission method at a wavelength of 4000 cm-1 to 500 cm-1 using a FTIR spectrophotometer. Digitized spectral data were submitted to neural networks training, until an error of less than 0.05 was obtained and than used for identification of isolates.
Results. The utility of neural networks has been determined based on the identification of 10 reference strains and 24 bacterial strains of the genus Leuconostoc isolated from food products. The isolated strains have been identified by PCR-based method using species-specific primers. The use of artificial neural networks in FTIR spectral analyses as the most advanced chemometric method supported the correct identification of 83-92% bacteria of the genus Leuconostoc at the species level.

Conclusions. The discussed method may be deployed in analytical laboratories for identifying lactic acid bacteria at the genus, species and subspecies level, for monitoring the purity of cultures in strain collections and for fast screening of selected bacterial groups. FTIR delivers a variety of advantages, including simple technology, low cost, high specificity and a wide range of industrial applications.

 

Keywords: bacteria of the genus Leuconostoc, FTIR spectra, PCR, artificial neural networks
pub/.pdf Full text available in english in Adobe Acrobat format:
http://www.food.actapol.net/issue3/volume/1_3_2011.pdf

For citation:

MLA Dziuba, Bartłomiej. "Identification of selected Leuconostoc species with the use of FTIR spectroscopy and artificial neural networks." Acta Sci.Pol. Technol. Aliment. 10.3 (2011): 275-285.
APA Dziuba B. (2011). Identification of selected Leuconostoc species with the use of FTIR spectroscopy and artificial neural networks. Acta Sci.Pol. Technol. Aliment. 10 (3), 275-285
ISO 690 DZIUBA, Bartłomiej. Identification of selected Leuconostoc species with the use of FTIR spectroscopy and artificial neural networks. Acta Sci.Pol. Technol. Aliment., 2011, 10.3: 275-285.