Metabolomics

, Volume 7, Issue 4, pp 500–508

Ambient mass spectrometry employing a DART ion source for metabolomic fingerprinting/profiling: a powerful tool for beer origin recognition

  • Tomas Cajka
  • Katerina Riddellova
  • Monika Tomaniova
  • Jana Hajslova
Original Article

Abstract

A metabolomic fingerprinting/profiling generated by ambient mass spectrometry (MS) employing a direct analysis in real time (DART) ion source coupled to high-resolution time-of-flight mass spectrometry (TOFMS) was employed as a tool for beer origin recognition. In a first step, the DART–TOFMS instrumental conditions were optimized to obtain the broadest possible representation of ionizable compounds occurring in beer samples (direct measurement, no sample preparation). In the next step, metabolomic profiles (mass spectra) of a large set of different beer brands (Trappist and non-Trappist specialty beers) were acquired. In the final phase, the experimental data were analyzed using partial least squares discriminant analysis (PLS-DA), linear discriminant analysis (LDA), and artificial neural networks with multilayer perceptrons (ANN-MLP) with the aim of distinguishing (i) the beers labeled as Rochefort 8; (ii) a group consisting of Rochefort 6, 8, 10 beers; and (iii) Trappist beers. The best prediction ability was obtained for the model that distinguished the group of Rochefort 6, 8, 10 beers from the rest of beers. In this case, all chemometric tools employed provided ≥95% correct classification. The current study showed that DART–TOFMS metabolomic fingerprinting/profiling is a powerful analytical strategy enabling quality monitoring/authenticity assessment to be conducted in real time.

Keywords

Beer Authenticity Traceability Direct analysis in real time Mass spectrometry Multivariate analysis Metabolomic fingerprinting/profiling 

Supplementary material

11306_2010_266_MOESM1_ESM.doc (48 kb)
Supplementary material 1 (DOC 47 kb)
11306_2010_266_MOESM2_ESM.doc (30 kb)
Supplementary material 2 (DOC 30 kb)

References

  1. Almeida, C., Duarte, I. F., Barros, A., Rodrigues, J., Spraul, M., & Gil, A. M. (2006). Composition of beer by 1H NMR spectroscopy: effects of brewing site and date of production. Journal of Agriculture and Food Chemistry, 54, 700–706.CrossRefGoogle Scholar
  2. Araujo, A. S., da Rocha, L. L., Tomazela, D. M., Sawaya, A. C. H. F., Almeida, R. R., Catharino, R. R., et al. (2005). Electrospray ionization mass spectrometry fingerprinting of beer. Analyst, 130, 884–889.PubMedCrossRefGoogle Scholar
  3. Aursand, M., Standal, I. B., & Axelson, D. E. (2007). High-resolution 13C nuclear magnetic resonance spectroscopy pattern recognition of fish oil capsules. Journal of Agriculture and Food Chemistry, 55, 38–47.CrossRefGoogle Scholar
  4. Berrueta, L. A., Alonso-Salces, R. M., & Heberger, K. (2007). Supervised pattern recognition in food analysis. Journal of Chromatography A, 1158, 196–214.PubMedCrossRefGoogle Scholar
  5. Cajka, T., Hajslova, J., Pudil, F., & Riddellova, K. (2009). Traceability of honey origin based on volatiles pattern processing by artificial neural networks. Journal of Chromatography A, 1216, 1458–1462.PubMedCrossRefGoogle Scholar
  6. Cajka, T., Riddellova, K., Klimankova, E., Cerna, M., Pudil, F., & Hajslova, J. (2010a). Traceability of olive oil based on volatiles pattern and multivariate analysis. Food Chemistry, 121, 282–289.CrossRefGoogle Scholar
  7. Cajka, T., Riddellova, K., Tomaniova, M., & Hajslova, J. (2010b). Recognition of beer brand based on multivariate analysis of volatile fingerprint. Journal of Chromatography A, 1217, 4195–4203.PubMedCrossRefGoogle Scholar
  8. Calderone, G., Guillou, C., Reniero, F., & Naulet, N. (2007). Helping to authenticate sparkling drinks with 13C/12C of CO2 by gas chromatography-isotope ratio mass spectrometry. Food Research International, 40, 324–331.CrossRefGoogle Scholar
  9. Cevallos-Cevallos, J. M., Reyes-De-Corcuera, J. I., Etxeberria, E., Danyluk, M. D., & Rodrick, G. E. (2009). Metabolomic analysis in food science: a review. Trends in Food Science & Technology, 20, 557–566.CrossRefGoogle Scholar
  10. Cody, R. B., Laramee, J. A., & Durst, H. D. (2005). Versatile new ion source for the analysis of materials in open air under ambient conditions. Analytical Chemistry, 77, 2297–2302.PubMedCrossRefGoogle Scholar
  11. Cuny, M., Le Gall, G., Colquhoun, I. J., Lees, M., & Rutledge, D. N. (2007). Evolving window zone selection method followed by independent component analysis as useful chemometric tools to discriminate between grapefruit juice, orange juice and blends. Analytica Chimica Acta, 597, 203–213.PubMedCrossRefGoogle Scholar
  12. Cuny, M., Vigneau, E., Le Gall, G., Colquhoun, I., Lees, M., & Rutledge, D. N. (2008). Fruit juice authentication by 1H NMR spectroscopy in combination with different chemometric tools. Analytical and Bioanalytical Chemistry, 390, 419–427.PubMedCrossRefGoogle Scholar
  13. da Silva, G. A., Augusto, F., & Poppi, R. J. (2008). Exploratory analysis of the volatile profile of beers by HS–SPME–GC. Food Chemistry, 111, 1057–1063.CrossRefGoogle Scholar
  14. Erbe, T., & Bruckner, H. (2000). Chromatographic determination of amino acid enantiomers in beers and raw materials used for their manufacture. Journal of Chromatography A, 881, 81–91.PubMedCrossRefGoogle Scholar
  15. Hajslova, J., Cajka, T., & Vaclavik, L. (2010). Challenging applications offered by direct analysis in real time (DART) in food quality and safety analysis. Trends in Analytical Chemistry (in press). doi: 10.1016/j.trac.2010.11.001.
  16. Hutton, W. C., Garbow, J. R., & Hayes, T. R. (1999). Nondestructive NMR determination of oil composition in transformed canola seeds. Lipids, 34, 1339–1346.PubMedCrossRefGoogle Scholar
  17. Kabelova, I., Dvorakova, M., Cizkova, H., Dostalek, P., & Melzoch, K. (2008). Determination of free amino acids in beers: A comparison of Czech and foreign brands. Journal of Food Composition and Analysis, 21, 736–741.CrossRefGoogle Scholar
  18. Lachenmeier, D. W. (2007). Rapid quality control of spirit drinks and beer using multivariate data analysis of Fourier transform infrared spectra. Food Chemistry, 101, 825–832.CrossRefGoogle Scholar
  19. Lachenmeier, D. W., Frank, W., Humpfer, E., Schafer, H., Keller, S., Mortter, M., et al. (2005). Quality control of beer using high-resolution nuclear magnetic resonance spectroscopy and multivariate analysis. European Food Research and Technology, 220, 215–221.CrossRefGoogle Scholar
  20. Le Gall, G., Puaud, M., & Colquhoun, I. J. (2001). Discrimination between orange juice and pulp wash by 1H Nuclear Magnetic Resonance spectroscopy: identification of marker compounds. Journal of Agriculture and Food Chemistry, 49, 580–588.CrossRefGoogle Scholar
  21. Mattarucchi, E., Stocchero, M., Moreno-Rojas, J.M., Giordano, G., Reniero, F., & Guillou, C. (2010). Authentication of Trappist beers by LC-MS fingerprints and multivariate data analysis. Journal of Agricultural and Food Chemistry, 58, 12089–12095.CrossRefGoogle Scholar
  22. McEwen, C. N., McKay, R. G., & Larsen, B. S. (2005). Analysis of solids, liquids, and biological tissues using solids probe introduction at atmospheric pressure on commercial LC/MS instruments. Analytical Chemistry, 77, 7826–7831.PubMedCrossRefGoogle Scholar
  23. Nord, L. I., Vaag, P., & Duus, J. O. (2004). Quantification of organic and amino acids in beer by 1H NMR spectroscopy. Analytical Chemistry, 76, 4790–4798.PubMedCrossRefGoogle Scholar
  24. Obruca, S., Marova, I., Parilova, K., Muller, L., Zdrahal, Z., & Mikulikova, R. (2009). A contribution to analysis of “Czech beer” authenticity. Czech Journal of Food Sciences, 27, S323–S326.Google Scholar
  25. Ogrinc, N., Kosir, I. J., Spangenberg, J. E., & Kidric, J. (2003). The application of NMR and MS methods for detection of adulteration of wine, fruit juices and olive oil: A review. Analytical and Bioanalytical Chemistry, 376, 424–430.PubMedCrossRefGoogle Scholar
  26. Prestes, R. A., Colnago, L. A., Forato, L. A., Vizzotto, L., Novotny, E. H., & Carrilho, E. (2007). A rapid and automated low resolution NMR method to analyze oil quality in intact oilseeds. Analytica Chimica Acta, 596, 325–329.PubMedCrossRefGoogle Scholar
  27. Rossmann, A. (2001). Determination of stable isotope ratios in food analysis. Food Reviews International, 17, 347–381.CrossRefGoogle Scholar
  28. Setkova, L., Risticevic, S., & Pawliszyn, J. (2007). Rapid headspace solid-phase microextraction-gas chromatographic–time-of-flight mass spectrometric method for qualitative profiling of ice wine volatile fraction: II: Classification of Canadian and Czech ice wines using statistical evaluation of the data. Journal of Chromatography A, 1147, 224–240.PubMedCrossRefGoogle Scholar
  29. Takats, Z., Wiseman, J. M., Gologan, B., & Cooks, R. G. (2004). Mass spectrometry sampling under ambient conditions with desorption electrospray ionization. Science, 306, 471–473.PubMedCrossRefGoogle Scholar
  30. Vaclavik, L., Cajka, T., Hrbek, V., & Hajslova, J. (2009). Ambient mass spectrometry employing direct analysis in real time (DART) ion source for olive oil quality and authenticity assessment. Analytica Chimica Acta, 645, 56–63.PubMedCrossRefGoogle Scholar
  31. Venter, A., Nefliu, M., & Cooks, R. G. (2008). Ambient desorption ionization mass spectrometry. Trends in Analytical Chemistry, 27, 284–290.CrossRefGoogle Scholar
  32. Weston, D. J. (2010). Ambient ionization mass spectrometry: current understanding of mechanistic theory; analytical performance and application areas. Analyst, 135, 661–668.PubMedCrossRefGoogle Scholar
  33. Wishart, D. S. (2008). Metabolomics: applications to food science and nutrition research. Trends in Food Science & Technology, 17, 482–493.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Tomas Cajka
    • 1
  • Katerina Riddellova
    • 1
  • Monika Tomaniova
    • 1
  • Jana Hajslova
    • 1
  1. 1.Institute of Chemical Technology Prague, Faculty of Food and Biochemical Technology, Department of Food Chemistry and AnalysisPrague 6Czech Republic

Personalised recommendations