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Varietal classification of white wines by fluorescence spectroscopy

Abstract

The Slovak Tokaj region is one of the producers of high-quality white wine having protected designations of origin. The main grape varieties of this region are Furmint, Lipovina and Muscat blanc, which have specific sensory characteristics. This research work presents a strategy for the classification of three mentioned varieties of white wines using fluorescence spectroscopy with chemometrics. Emission and synchronous fluorescence spectra were obtained for bulk as well as diluted samples, principal component analysis (PCA) was applied for exploratory analysis and the scores of the selected PCs were used in linear discriminant analysis (LDA). For undiluted samples, the best PCA-LDA models based on either emission spectra excited at 370 nm or synchronous fluorescence spectra obtained at wavelength difference of 40 and 100 nm provided total correct classifications of 100, 100 and 93% for the calibration, validation and prediction steps, respectively. For diluted samples, the best PCA-LDA models (excitation at 280 nm; wavelength difference of 40 nm) again provided total correct classifications as mentioned above.

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References

  • Agati G, Matteini P, Oliveira J, de Freitas V, Mateus N (2013) Fluorescence approach for measuring anthocyanins and derived pigments in red wine. J Agric Food Chem 61:10156–10162

    CAS  Article  Google Scholar 

  • Airado-Rodríguez D, Galeano-Díaz T, Durán-Merás I, Wold JP (2009) Usefulness of fluorescence excitation–emission matrices in combination with PARAFAC, as fingerprints of red wines. J Agric Food Chem 57:1711–1720

    Article  Google Scholar 

  • Azcarate SM, de Araújo GA, Alcaraz MR, Ugulino de Araújo MC, Camiña JM, Goicoechea HC (2015) Modeling excitation–emission fluorescence matrices with pattern recognition algorithms for classification of Argentine white wines according grape variety. Food Chem 184:214–219

    CAS  Article  Google Scholar 

  • Cabrera-Bañegil M, Hurtado-Sánchez MC, Galeano-Díaz T, Durán-Merás I (2017) Front-face fluorescence spectroscopy combined with second-order multivariate algorithms for the quantification of polyphenols in red wine samples. Food Chem 220:168–176

    Article  Google Scholar 

  • Cozzolino D, Smyth HE, Cynkar W, Dambergs RG, Gishen M (2005) Usefulness of chemometrics and mass spectrometry-based electronic nose to classify Australian white wines by their varietal origin. Talanta 68:382–387

    CAS  Article  Google Scholar 

  • del Caro A, Fanara C, Genovese A, Moio L, Piga A, Piombino P (2012) Free and enzymatically hydrolysed volatile compounds of sweet wines from Malvasia and Muscat grapes (Vitis vinifera L.) grown in Sardinia. S Afr J Enol Vitic 33:115–121

    Google Scholar 

  • Drawert F, Leupold G, Lessing V, Kerènyi Z (1976) Gaschromatographische Bestimmung der Inhaltsstoffe von Gärungsgetränken. VI. Quantitative gaschromatographische Bestimmung von Neutralstoffen (Kohlenhydraten) und phenolischen Verbindungen in Tokajer Weinen. Z Lebensm Unters Forsch 162:407–414

    CAS  Article  Google Scholar 

  • Dufour E, Letort A, Laguet A, Lebecque A, Serra JN (2006) Investigation of variety, typicality and vintage of French and German wines using front-face fluorescence spectroscopy. Anal Chim Acta 563:292–299

    CAS  Article  Google Scholar 

  • Eftimová J (2009) Sensitivity of Tokay vine varieties to Plasmopara Viticola (Berk and Curt.) Berk. and De Toni. Acta Fytotechnica et Zootechnica 1:9–12

    Google Scholar 

  • Elcoroaristizabal S, Callejón RM, Amigo JM, Ocaña-González JA, Lourdes Morales M, Ubeda C (2016) Fluorescence excitation–emission matrix spectroscopy as a tool for determining quality of sparkling wines. Food Chem 206:284–290

    CAS  Article  Google Scholar 

  • Geana EI, Ionete RE, Tudorache A, Pasa R, Postolache E, Ranca A (2011) Phenolic contents of Romanian wines with different geographical origins. Asian J Chem 23:5197–5201

    CAS  Google Scholar 

  • Godoy-Caballero MP, Airado-Rodríguez D, Durán-Merás I, Galeano-Díaz T (2010) Sensitized synchronous fluorimetric determination of trans-resveratrol and trans-piceid in red wine based on their immobilization on nylon membranes. Talanta 82:1733–1741

    CAS  Article  Google Scholar 

  • Hajós G, Sass-Kiss A, Szerdahelyi E, Bardocz S (2000) Changes in biogenic amine content of Tokaj grapes, wines, and Aszu-wines. J Food Sci 65:1142–1144

    Article  Google Scholar 

  • Heras-Roger J, Díaz-Romero C, Darias-Martín J (2016) A comprehensive study of red wine properties according to variety. Food Chem 196:1224–1231

    CAS  Article  Google Scholar 

  • Jackson RS (2014) Wine science: grape species and varieties, 4th edn. Elsevier, Amsterdam, pp 21–67

    Book  Google Scholar 

  • Jakubíková M, Sádecká J, Kleinová A (2017) On the use of the fluorescence, ultraviolet–visible and near infrared spectroscopy with chemometrics for the discrimination between plum brandies of different varietal origins. Food Chem 239:889–897

    Article  Google Scholar 

  • Kennard RW, Stone LA (1969) Computer aided design of experiments. Technometrics 11:137–148

    Article  Google Scholar 

  • Longobardi F, Innamorato V, Di Gioia A, Ventrella A, Lippolis V, Logrieco AF, Catucci L, Agostiano A (2017) Geographical origin discrimination of lentils (Lens culinaris Medik.) using 1H NMR fingerprinting and multivariate statistical analyses. Food Chem 237:743–748

    CAS  Article  Google Scholar 

  • Lukić I, Lottic C, Vrhovsek U (2017) Evolution of free and bound volatile aroma compounds and phenols during fermentation of Muscat blanc grape juice with and without skins. Food Chem 232:25–35

    Article  Google Scholar 

  • Martin C, Bruneel JL, Castet F, Fritsch A, Teissedre PL, Jourdes M, Guillaume F (2017) Spectroscopic and theoretical investigations of phenolic acids in white wines. Food Chem 221:568–575

    CAS  Article  Google Scholar 

  • Mutavdžić M, Mutavdžić D, Radotić K (2013) Differentiation of wine commercial samples by using fluorescence spectroscopy and multivariate analysis. Acta Agric Serb 36:169–177

    Google Scholar 

  • Nedeljkovic A, Tomasevic I, Miocinovic J, Pudja P (2017) Feasibility of discrimination of dairy creams and cream-like analogues using Raman spectroscopy and chemometric analysis. Food Chem 232:487–492

    CAS  Article  Google Scholar 

  • Pour Nikfardjam MS, László G, Dietrich H (2003) Polyphenols and antioxidative capacity in Hungarian Tokaj wine. Mitt Klosterneuburg 53:159–165

    CAS  Google Scholar 

  • Ríos-Reina R, Elcoroaristizabal S, Ocaña-González JA, García-González DL, Amigo JM, Callejón RM (2017) Characterization and authentication of Spanish PDO wine vinegars using multidimensional fluorescence and chemometrics. Food Chem 230:108–116

    Article  Google Scholar 

  • Rodríguez-Delgado MA, Malovaná S, Pérez JP, Borges T, García Montelongo FJ (2001) Separation of phenolic compounds by high-performance liquid chromatography with absorbance and fluorimetric detection. J Chromatogr A 912:249–257

    Article  Google Scholar 

  • Saad R, Bouveresse DJR, Locquet N, Rutledge DN (2016) Using pH variations to improve the discrimination of wines by 3D front face fluorescence spectroscopy associated to Independent Components Analysis. Talanta 153:278–284

    CAS  Article  Google Scholar 

  • Sádecká J, Jakubíková M, Májek P (2018) Fluorescence spectroscopy for discrimination of botrytized wines. Food Control 88:75–84

    Article  Google Scholar 

  • Sass-Kiss A, Szerdahelyi E, Hajós G (2000) Study of biologically active amines in grapes and wines by HPLC. Chromatographia 51:S316–S320

    CAS  Article  Google Scholar 

  • Sazhina NN, Misin VM, Korotkova EI, Voronova OA, Dorozhko EV (2014) Determination of total antioxidant content in various drinks by amperometry. Procedia Chem 10:64–73

    CAS  Article  Google Scholar 

  • Sergiel I, Pohl P, Biesaga M, Mironczyk A (2014) Suitability of three-dimensional synchronous fluorescence spectroscopy for fingerprint analysis of honey samples with reference to their phenolic profiles. Food Chem 145:319–326

    CAS  Article  Google Scholar 

  • Silvestri M, Elia A, Bertelli D, Salvatore E, Durante C, Li Vigni M, Marchetti A, Cocchi M (2014) A mid level data fusion strategy for the Varietal Classification of Lambrusco PDO wines. Chemometr Intell Lab Syst 137:181–189

    CAS  Article  Google Scholar 

  • Wan Y, Pan F, Shen M (2012) Identification of Jiangxi wines by three-dimensional fluorescence fingerprints. Spectrochim Acta A 96:605–610

    CAS  Article  Google Scholar 

  • Yin C, Li H, Ding C, Wang H (2009) Preliminary investigation of variety, brewery and vintage of wines using three-dimensional fluorescence spectroscopy. Food Sci Technol Res 15:27–38

    CAS  Article  Google Scholar 

  • Žiak Ľ, Sádecká J, Májek P, Hroboňová K (2014) Simultaneous determination of phenolic acids and scopoletin in brandies using synchronous fluorescence spectrometry coupled with partial least squares. Food Anal Method 7:563–570

    Article  Google Scholar 

  • Ziółkowska A, Wąsowicz E, Jeleń HJ (2016) Differentiation of wines according to grape variety and geographical origin based on volatiles profiling using SPME-MS and SPME-GC/MS methods. Food Chem 213:714–720

    Article  Google Scholar 

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Acknowledgements

This research was supported by the Slovak Research and Development Agency under the contract No. APVV-15-0355. Authors would like to thank tokaj wine producers Ostrožovič spol. s.r.o. for their kind cooperation.

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Correspondence to Michaela Jakubíková.

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Sádecká, J., Jakubíková, M. Varietal classification of white wines by fluorescence spectroscopy. J Food Sci Technol 57, 2545–2553 (2020). https://doi.org/10.1007/s13197-020-04291-y

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  • DOI: https://doi.org/10.1007/s13197-020-04291-y

Keywords

  • White wines
  • Varietal classification
  • Fluorescence
  • Principal component analysis
  • Linear discriminant analysis