Identification of lactic acid bacteria and propionic acid bacteria using FTIR spectroscopy and artificial neural networks

Food Technology and Biotechnology

Volumn 50, Issue 4, 2012, Pages 399-405

  Dziuba, Bartlomiej ^a   Nalepa, Beata ^a  

^a UNIVERSITY OF WARMIA AND MAZURY IN OLSZTYN   (Poland)

Author keywords

Artificial neural networks; FTIR spectroscopy; Lactic acid bacteria; Propionic acid bacteria

Indexed keywords

BACTERIAL IDENTIFICATIONS; BACTERIAL STRAINS; FIRST DERIVATIVE; FOOD PROCESSING INDUSTRY; FTIR SPECTROSCOPY; LACTIC ACID BACTERIA; PROBABILISTIC NEURAL NETWORKS; PROPIONIBACTERIUM;

BACTERIA; FOOD PROCESSING; FOOD PRODUCTS; LACTIC ACID; NEURAL NETWORKS; PROPIONIC ACID; SATURATED FATTY ACIDS;

FOURIER TRANSFORM INFRARED SPECTROSCOPY;

BACTERIA (MICROORGANISMS); LACTOBACILLUS; LACTOCOCCUS; LEUCONOSTOC; PROPIONIBACTERIUM; STREPTOCOCCUS;

EID: 84873189429     PISSN: 13309862     EISSN: 13342606     Source Type: Journal    
DOI: None     Document Type: Article

References (33)

1. D. Naumann, H. Labischinski, P. Giesbrecht: The Characterization of Microorganisms by Fourier-Transform Infrared Spectroscopy (FT-IR). In: Modern Techniques for Rapid Microbiological Analysis, W. H. Nelson (Ed.), VCH Publishers, New York, NY, USA (1991) pp. 43-96.
2. J. Samelis, A. Bleicher, C. Delbès-Paus, A. Kakouri, K. Neuhaus, M. C. Montel, FTIR-based polyphasic identification of lactic acid bacteria isolated from traditional Greek Graviera cheese, Food Microbiol. 28 (2011) 76-83.
3. C. Amiel, L. Mariey, M. C. Curk-Daubié, P. Pichon, J. Travert, Potentiality of fourier transform infrared spectroscopy (FTIR) for discrimination and identification of dairy lactic acid bacteria, Lait, 80 (2000) 445-459.
4. C. Amiel, L. Mariey, C. Denis, P. Pichon, J. Travert, FTIR spectroscopy and taxonomic purpose: Contribution to the classification of lactic acid bacteria, Lait, 81 (2001) 249-255. (Pubitemid 33589317)
5. R. Goodacre, E. M. Timmins, R. Burton, N. Kaderbhai, A. M. Woodward, D. B. Kell P. J. Rooney, Rapid identification of urinary tract infection bacteria using hyperspectral whole-organism fingerprinting and artificial neural networks, Microbiology, 144 (1998) 1157-1170. (Pubitemid 28233819)
6. C. Kirschner, K. Maquelin, P. Pina, N. A. Ngo-Thi, L. P. Choo-Smith, G. D. Sockalingum, Classification and identification of enterococci: A comparative phenotypic, genotypic, and vibrational spectroscopic study, J. Clin. Microbiol. 39 (2001) 1763-1770. (Pubitemid 32417017)
7. K. Tintelnot, G. Haase, M. Seibold, F. Bergmann, M. Staemmler, T. Franz, D. Naumann, Evaluation of phenotypic markers for selection and identification of Candida dubliniensis, J. Clin. Microbiol. 38 (2000) 1599-1608. (Pubitemid 30216696)
8. T. Udelhoven, D. Naumann, J. Schmitt, Development of hierarchical classification systems with artificial neural networks and FT-IR spectra for the identification of bacteria, Appl. Spectrosc. 54 (2000) 1471-1479.
9. M. Wenning, N. R. Büchl, S. Scherer, Species and strain identification of lactic acid bacteria using FTIR spectroscopy and artificial neural networks, J. Biophotonics, 3 (2010) 493-505.
10. R. Tadeusiwicz, P. Lula, STATISTICA Neural Network v. 4.01: Course Materials, Stat Soft Inc, Warsaw, Poland (2002).
11. B. Dziuba, A. Babuchowski, M. Niklewicz, B. Brzozowski, FTIR spectral characteristics of lactic acid bacteria: A spectral library, Milchwissenschaft, 61 (2006) 146-149.
12. B. Dziuba, A. Babuchowski, M. Dziuba, D. Nalȩcz, Identification of lactic acid bacteria using FTIR spectroscopy and artificial networks, Milchwissenschaft, 62 (2007) 28-32. (Pubitemid 46155445)
13. B. Dziuba, A. Babuchowski, D. Nal Qcz, M. Niklewicz, Identification of lactic acid bacteria using FTIR spectroscopy and cluster analysis, Int. Dairy J. 17 (2007) 183-189. (Pubitemid 44708753)
14. B. Dziuba, Identification of Lactobacillus strains at the species level using FTIR spectroscopy and artificial neural networks, Pol. J. Food. Nutr. Sci. 57 (2007) 301-306.
15. B. Dziuba, Identification of selected Leuconostoc species with the use of FTIR spectroscopy and artificial neural networks, Acta Sci. Pol. Technol. Aliment. 10 (2011) 275-285.
16. I. Filya, E. Sucu, A. Karabulut, The effect of Propionibacterium acidipropionici, with or without Lactobacillus plantarum, on the fermentation and aerobic stability of wheat, sorghum and maize silages, J. Appl. Microbiol. 97 (2004) 818-826. (Pubitemid 39331588)
17. R. J. Merry, D. R. Davies, Propionibacteria and their role in the biological control of aerobic spoilage in silage, Lait, 79 (1999) 149-164. (Pubitemid 129511859)
18. H. Holo, T. Faye, D. A. Brede, T. Nilsen, I. Odegard, T. Langsrud et al, Bacteriocins of propionic acid bacteria, Lait, 82 (2002) 59-68.
19. J. Hugenholtz, J. Hunik, H. Santos, E. Smid, Nutraceutical production by propionibacteria, Lait, 82 (2002) 103-112.
20. K. Hojo, R. Watanabe, T. Mori, N. Taketomo, Quantitative measurement of tetrahydromenaquinone-9 in cheese fermented by propionibacteria, J. Dairy Sci. 90 (2007) 4078-4083. (Pubitemid 350045182)
21. D. F. M. Daly, P. L. H. McSweeney, J. J. Sheehan, Split defect and secondary fermentation in Swiss-type cheeses - A review, Dairy Sci. Technol. 90 (2010) 3-26.
22. S. Dubernet, N. Desmasures, M. Gueguen, A PCR-based method for identification of lactobacilli at genus level, FEMS Microbiol. Lett. 214 (2002) 271-275. (Pubitemid 35287050)
23. M. C. Macián, E. Chenoll, R. Aznar, Simultaneous detection of Carnobacterium and Leuconostoc in meat products by multiplex PCR, J. Appl. Microbiol. 97 (2004) 384-394. (Pubitemid 38998671)
24. F. Rossi, S. Torriani, F. Dellaglio, Genus-and species-specific PCR-based detection of dairy propionibacteria in environmental samples by using primers targeted to the genes encoding 16S rRNA, Appl. Environ. Microbiol. 65 (1999) 4241-4244.
25. Z. Y. Pu, M. Dobos, G. K. Y. Limsowtin, I. B. Powell, Integrated polymerase chain reaction-based procedures for the detection and identification of species and subspecies of the Gram-positive bacterial genus Lactococcus, J. Appl. Microbiol. 93 (2002) 353-361. (Pubitemid 34989155)
26. D. F. Specht, Probabilistic neural networks, Neural Networks, 3 (1990) 109-118.
27. C. Bishop: Neural Networks for Pattern Recognition, Oxford University Press, Oxford, UK (1995).
28. L. Mariey, J. P. Signolle, C. Amiel, J. Travert, Discrimination, classification, identification of microorganisms using FTIR spectroscopy and chemometrics, Vib. Spectrosc. 26 (2001) 151-159. (Pubitemid 33018466)
29. K. Maquelin, C. Kirschner, L. P. Choo-Smith, N. A. Ngo-Thi, T. Van Vreeswijk, M. Stammler et al., Prospective study of the performance of vibrational spectroscopies for rapid identification of bacterial and fungal pathogens recovered from blood cultures, J. Clin. Microbiol. 41 (2003) 324-329. (Pubitemid 36098595)
30. B. Weinrichter, W. Luginnbuhl, H. Rohm, J. Jimeno, Differentiation of facultatively heterofermentative lactobacilli from plants, milk, and hard type cheeses by SDS-PAGE, RAPD, FTIR, energy source utilization and autolysis type, Lebensm. Wiss. Technol. 34 (2001) 556-566. (Pubitemid 34415931)
31. E. Garcia-Caurel, J. Nguyen, L. Schwartz, B. Drévillon, Application of FTIR ellipsometry to detect and classify microorganisms, Thin Solid Films, 455-456 (2004) 722-725.
32. S. Goerges, J. Mounier, M. C. Rea, R. Gelsomino, V. Heise, R. Beduhn et al, Commercial ripening starter microorganisms inoculated into cheese milk do not successfully establish themselves in the resident microbial ripening consortia of a South German red smear cheese, Appl. Environ. Microbiol. 74 (2008) 2210-2217. (Pubitemid 351522076)
33. C. A. Rebuffo, J. Schmitt, M. Wenning, F. Von Stetten, S. Scherer, Reliable and rapid identification of Listeria monocytogenes and Listeria species by artificial neural network-based Fourier transform infrared spectroscopy, Appl. Environ. Microbiol. 72 (2006) 994-1000. (Pubitemid 43271201)