Skip to main content
Log in

The Parallel Factor Analysis of Beer Fluorescence

  • ORIGINAL ARTICLE
  • Published:
Journal of Fluorescence Aims and scope Submit manuscript

Abstract

Fluorescence excitation-emission matrices were measured for 111 samples of different types of beer and studied by the parallel factor analysis (PARAFAC). The 5-component PARAFAC model was found to suitably describes the beer fluorescence, accounting for 99.4% of the fluorescence variance in the measured set of samples, and providing the completely resolved excitation and emission spectra of each component. The model was chosen based on a model’s core consistency and split-half analysis. It is shown that beer fluorescence is the sum of fluorescence of aromatic amino acids (tryptophan, tyrosine, and phenylalanine), different forms of vitamin B, and phenolic compounds. Obtained PARAFAC model of beer fluorescence demonstrated the potential for the quantification and quality analysis of beer fluorophores and classification of different beer types.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Obara K, Mizutani M, Hitomi Y, Yajima H, Kondo K (2009) Isohumolones, the bitter component of beer, improve hyperglycemia and decrease body fat in Japanese subjects with prediabetes. Clin Nutr 28(3):278–284. https://doi.org/10.1016/j.clnu.2009.03.012

    Article  CAS  PubMed  Google Scholar 

  2. Gerhäuser C (2005) Beer constituents as potential cancer chemopreventive agents. Eur J Cancer 41(13):1941–1954. https://doi.org/10.1016/j.ejca.2005.04.012

    Article  CAS  PubMed  Google Scholar 

  3. Rendall R, Reis MS, Cristina Pereira A, Pestana C, Pereira V, Marques JC (2015) Chemometric analysis of the volatile fraction evolution of Portuguese beer under shelf storage conditions. Chemom Intell Lab Syst 142:131–142. https://doi.org/10.1016/j.chemolab.2015.01.015

    Article  CAS  Google Scholar 

  4. Alcázar A, Jurado JM, Palacios-Morillo A, de Pablos F, Martín MJ (2012) Differentiation of blonde beers according to chemical quality indicators by means of pattern recognition techniques. Food Anal Methods 5(4):795–799. https://doi.org/10.1007/s12161-011-9313-2

    Article  Google Scholar 

  5. Cajka T, Riddellova K, Tomaniova M, Hajslova J (2010) Recognition of beer brand based on multivariate analysis of volatile fingerprint. J Chromatogr A 1217(25):4195–4203. https://doi.org/10.1016/j.chroma.2009.12.049

    Article  CAS  PubMed  Google Scholar 

  6. Floridi S, Montanari L, Marconi O, Fantozzi P (2003) Determination of free phenolic acids in wort and beer by coulometric array detection. J Agric Food Chem 51(6):1548–1554. https://doi.org/10.1021/jf0260040

    Article  CAS  PubMed  Google Scholar 

  7. Rehová L, Skeríková V, Jandera P (2004) Optimisation of gradient HPLC analysis of phenolic compounds and flavonoids in beer using a CoulArray detector. J Sep Sci 27(15–16):1345–1359. https://doi.org/10.1002/jssc.200401916

    Article  CAS  PubMed  Google Scholar 

  8. Nardini M, Ghiselli A (2004) Determination of free and bound phenolic acids in beer. Food Chem 84(1):137–143. https://doi.org/10.1016/S0308-8146(03)00257-7

    Article  CAS  Google Scholar 

  9. Vanbeneden N, Delvaux F, Delvaux FR (2006) Determination of hydroxycinnamic acids and volatile phenols in wort and beer by isocratic high-performance liquid chromatography using electrochemical detection. J Chromatogr A 1136(2):237–242. https://doi.org/10.1016/j.chroma.2006.11.001

    Article  CAS  PubMed  Google Scholar 

  10. Bartolomé B, Peña-Neira A, Gómez-Cordovés C (2000) Phenolics and related substances in alcohol-free beers. Eur Food Res Technol 210(6):419–423. https://doi.org/10.1007/s002170050574

    Article  Google Scholar 

  11. Ceslova L, Holcapek M, Fidler M, Drstickova J, Lisa M (2009) Characterization of prenylflavonoids and hop bitter acids in various classes of Czech beers and hop extracts using high-performance liquid chromatography–mass spectrometry. J Chromatogr A 1216(43):7249–7257. https://doi.org/10.1016/j.chroma.2009.09.022

    Article  CAS  PubMed  Google Scholar 

  12. Quifer-Rada P, Vallverdú-Queralt A, Martínez-Huélamo M, Chiva-Blanch G, Jáuregui O, Estruch R, Lamuela-Raventós R (2015) A comprehensive characterisation of beer polyphenols by high resolution mass spectrometry (LC–ESI-LTQ-Orbitrap-MS). Food Chem 169:336–343. https://doi.org/10.1016/j.foodchem.2014.07.154

    Article  CAS  PubMed  Google Scholar 

  13. Luterotti S, Kljak K (2010) Spectrophotometric estimation of total carotenoids in cereal grain products. Acta Chim Slov 57(4):781–787

    CAS  PubMed  Google Scholar 

  14. Sádecká J, Uríčková V, Hroboňová K, Májek P (2015) Classification of juniper-flavoured spirit drinks by multivariate analysis of spectroscopic and chromatographic data. Food Anal Methods 8(1):58–69. https://doi.org/10.1007/s12161-014-9869-8

    Article  Google Scholar 

  15. Almeida C, Duarte IF, Barros A, Rodrigues J, Spraul M, Gil AM (2006) Composition of beer by 1H NMR spectroscopy: effects of brewing site and date of production. J Agric Food Chem 54(3):700–706. https://doi.org/10.1021/jf0526947

    Article  CAS  PubMed  Google Scholar 

  16. Inon FA, Garrigues S, De la Guardia M (2006) Combination of mid- and near-infrared spectroscopy for the determination of the quality properties of beers. Anal Chim Acta 571:167–174. https://doi.org/10.1016/j.aca.2006.04.070

    Article  CAS  PubMed  Google Scholar 

  17. Lachenmeier DW (2007) Rapid quality control of spirit drinks and beer using multivariate data analysis of Fourier transform infrared spectra. Food Chem 101:825–832. https://doi.org/10.1016/j.foodchem.2005.12.032

    Article  CAS  Google Scholar 

  18. Christensen J, Norgaard L, Bro R, Englesen SB (2006) Multivariate autofluorescence of intact food systems. Chem Rev 106(6):1979–1989. https://doi.org/10.1021/cr050019q

    Article  CAS  PubMed  Google Scholar 

  19. Sadecka J, Jakubíkova M, Majek P (2018) Fluorescence spectroscopy for discrimination of botrytized wines. Food Control 88:75–84. https://doi.org/10.1016/j.foodcont.2017.12.033

    Article  CAS  Google Scholar 

  20. Lenhardt L, Zeković I, Dramićanin T, Dramićanin MD, Bro R (2014) Determination of the botanical origin of honey by front face synchronous fluorescence spectroscopy. Appl Spectrosc 68(5):557–563. https://doi.org/10.1366/13-07325

    Article  CAS  PubMed  Google Scholar 

  21. Sikorska E, Gliszczynska-Swigłl A, Insinska-Rak M, Khmelinskii I, De Keukeleire D, Sikorski M (2008) Simultaneous analysis of riboflavin and aromatic amino acids in beer using fluorescence and multivariate calibration methods. Anal Chim Acta 613(2):207–217. https://doi.org/10.1016/j.aca.2008.02.063

    Article  CAS  PubMed  Google Scholar 

  22. Sikorska E, Górecki T, Khmelinskii IV, Sikorski M, De Keukeleire D (2006) Monitoring beer during storage by fluorescence spectroscopy. Food Chem 96(4):632–639 https://lib.ugent.be/catalog/pug01:412896

    Article  CAS  Google Scholar 

  23. Tan J, Li R, Jiang ZT (2015) Chemometric classification of Chinese lager beers according to manufacturer based on data fusion of fluorescence, UV and visible spectroscopies. Food Chem 184:30–36. https://doi.org/10.1016/j.foodchem.2015.03.085

    Article  CAS  PubMed  Google Scholar 

  24. Sikorska E, Gorecki T, Khmelinskii IV, Sikorski M, De Keukeleire D (2004) Fluorescence spectroscopy for characterization and differentiation of beers. J Inst Brew 110(4):267–275. https://doi.org/10.1002/j.2050-0416.2004.tb00621.x

    Article  CAS  Google Scholar 

  25. Amigo JM, Marini F (2013) Multiway methods. In: Federico M (ed) Data handling in science and technology. Elsevier, Amsterdam, pp 265–313. https://doi.org/10.1016/B978-0-444-59528-7.00007-7

    Chapter  Google Scholar 

  26. Lenhardt L, Zeković I, Dramićanin T, Bro R, Dramićanin M (2018) Modeling food fluorescence with PARAFAC. In: Geddes CD (ed) Reviews in fluorescence 2017, reviews in fluorescence. Springer, Basel, pp 161–197. https://doi.org/10.1007/978-3-030-01569-5_8

    Chapter  Google Scholar 

  27. Bro R (1999) Exploratory study of sugar production using fluorescence spectroscopy and multi way analysis. Chemom Intell Lab Syst 46(2):133–147. https://doi.org/10.1016/S0169-7439(98)00181-6

    Article  CAS  Google Scholar 

  28. Callejón RM, Amigo JM, Pairo E, Garmón S, Ocaña JA, Morales ML (2012) Classification of Sherry vinegars by combining multidimensional fluorescence, PARAFAC and different classification approaches. Talanta 88:456–462. https://doi.org/10.1016/j.talanta.2011.11.014

    Article  CAS  PubMed  Google Scholar 

  29. Christensen J, Miquel Becker E, Frederiksen CS (2005) Fluorescence spectroscopy and PARAFAC in the analysis of yogurt. Chemom Intell Lab Syst 75(2):201–208. https://doi.org/10.1016/j.chemolab.2004.07.007

    Article  CAS  Google Scholar 

  30. Lenhardt L, Bro R, Zeković I, Dramićanin T, Dramićanin MD (2015) Fluorescence spectroscopy coupled with PARAFAC and PLS DA for characterization and classification of honey. Food Chem 175:284–291. https://doi.org/10.1016/j.foodchem.2014.11.162

    Article  CAS  PubMed  Google Scholar 

  31. Murphy KR, Stedmon CA, Graeber D, Bro R (2013) Fluorescence spectroscopy and multi-way techniques PARAFAC. Anal Methods 5(23):6557–6566. https://doi.org/10.1039/C3AY41160E

    Article  CAS  Google Scholar 

  32. Lenhardt L, Zeković I, Dramićanin T, Milićević B, Burojević J, Dramićanin MD (2017) Characterization of cereal flours by fluorescence spectroscopy coupled with PARAFAC. Food Chem 229:165–171. https://doi.org/10.1016/j.foodchem.2017.02.070

    Article  CAS  PubMed  Google Scholar 

  33. Elcoroaristizabal S, Bro R, García JA, Alonso L (2015) PARAFAC models of fluorescence data with scattering: a comparative study. Chemom Intell Lab Syst 142:124–130. https://doi.org/10.1016/j.chemolab.2015.01.017

    Article  CAS  Google Scholar 

  34. Bro R (1997) PARAFAC. Tutorial and applications. Chemom Intell Lab Syst 38(2):149–171. https://doi.org/10.1016/S0169-7439(97)00032-4

    Article  CAS  Google Scholar 

  35. Bro R, Kiers HAL (2003) A new efficient method for determining the number of components in PARAFAC models. J Chemom 17(5):274–286. https://doi.org/10.1002/cem.801

    Article  CAS  Google Scholar 

  36. Smilde A, Bro R, Geladi P (2004) Selecting the number of components. In: Multi-way analysis: applications in the chemical sciences. Wiley, Chichester, pp 156–166. (Chapter 7). https://doi.org/10.1002/0470012110.ch7

    Chapter  Google Scholar 

  37. Indahl UG, Martens H, Næs T (2007) From dummy regression to prior probabilities in PLS DA. J Chemom 21(12):529–536. https://doi.org/10.1002/cem.1061

    Article  CAS  Google Scholar 

  38. Nocairi H, Qannari EM, Vigneau E, Bertrand D (2005) Discrimination on latent components with respect to patterns. Application to multicollinear data. Comput Stat Data An 48(1):139–147. https://doi.org/10.1016/j.csda.2003.09.008

    Article  Google Scholar 

  39. de Ridder D, Tax DM, Lei B, Xu G, Feng M, Zou Y, van der Heijden F (2017) State estimation. In: Classification, parameter estimation and state estimation: in de Ridder D. Tax DM, Lei B, Xu G, Feng M, Zou Y, van der Heijden F (eds) An engineering approach using MatLab, 1st edn. Wiley, Chichester, pp 115–205. (Chapter 5). https://doi.org/10.1002/9781119152484.ch5

  40. Sikorska E, Khmelinskii I, Sikorski M (2009) Fluorescence methods for analysis of beer. In: Preedy VR (ed) Beer in health and disease prevention, 4th edn. Elsevier, London, pp 963–976

    Chapter  Google Scholar 

  41. Hough JS (1982) Malting and brewing science, Vol. 2: hopped wort and beer, chapter 22 chemical and physical properties of beer. Aspen Publishers, Gaithersburg, p 1982

    Book  Google Scholar 

  42. Pai TV, Sawant SY, Ghatak AA, Chaturvedi PA, Gupte AM, Desai NS (2013) Characterization of Indian beers: chemical composition and antioxidant potential. J Food Sci Technol 52(3):1414–1423. https://doi.org/10.1007/s13197-013-1152-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

Authors acknowledge the financial support of the Ministry of Education, Science and Technological Development of the Republic of Serbia (Project No: 45020).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Miroslav D. Dramićanin.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dramićanin, T., Zeković, I., Periša, J. et al. The Parallel Factor Analysis of Beer Fluorescence. J Fluoresc 29, 1103–1111 (2019). https://doi.org/10.1007/s10895-019-02421-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10895-019-02421-0

Keywords

Navigation