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Inorganic Materials

, Volume 54, Issue 14, pp 1435–1442 | Cite as

Application of Statistical Methods for Classification of Varietal and Regional Origin of White Wines

  • V. O. Titarenko
  • A. A. Khalafyan
  • Z. A. TemerdashevEmail author
  • A. A. Kaunova
  • E. A. Ivanovets
CONFORMITY ASSESSMENT. ACCREDITATION OF LABORATORIES
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Abstract

White wines of four wine-growing regions of Krasnodar region were studied by the ICP-AES method. Nineteen elements were identified in 153 samples of white wines of the Chardonnay, Riesling, and Muscat brands. Methods of statistical analysis demonstrated that, despite the complicated technological cycle of wine production (soil–grapes–juice–wine), information about the grape variety and the region of its origin is preserved in the totality of trace elements. Probabilistic statistical models were constructed to identify the grape variety and the region where it was grown by the concentrations of a certain set of microelements contained in wine. The proposed models are based on the assumption that the soil origin is an important factor determining the microelement composition in wine.

Keywords:

identification of regional and varietal origin of white wines content of trace elements in wines methods of classification trees discriminant analysis 

Notes

ACKNOWLEDGMENTS

The study was supported by the Russian Foundation for Basic Research (grant no. 18-03-00059); experiments were carried out with the use of scientific equipment of the Ecological and Analytical Center of the Kuban State University, unique identifier RFMEFI59317Х0008.

REFERENCES

  1. 1.
    Schlesier, K., Fauhl-Hassek, C., Forina, M., et al., Characterization and determination of the geographical origin of wines. Part I: Overview, Eur. Food Res. Technol., 2009, vol. 230, no. 1, pp. 1–13.CrossRefGoogle Scholar
  2. 2.
    Korovin, I.A., Panasyuk, A.L., et al., Vino i alkogol’nye napitki. Direktivy i reglamenty Evropeiskogo soyuza (Wine and Alcoholic Drinks. European Union Directives and Regulations), Moscow: Izd. Standartov, 2000.Google Scholar
  3. 3.
    Titarenko, V.O., Kaunova, A.A., Temerdashev, Z.A., and Popandopulo, V.G., Investigation of the correlation between the elemental content of grapes and the soil of the region of its growth, Anal. Kontrol’, 2016, vol. 20, no. 2, pp. 138–146.Google Scholar
  4. 4.
    Daniel, C. and Smyth, H., Analytical and chemometric-based methods to monitor and evaluate wine protected designation, Compr. Anal. Chem., 2013, vol. 60, pp. 385–408.CrossRefGoogle Scholar
  5. 5.
    Yakuba, Yu.F., Kaunova, A.A., Temerdashev, Z.A., et al., Grape wines, problems of their quality and regional origin evaluation, Anal. Kontrol’, 2014, vol. 18, no. 4, pp. 344–373.Google Scholar
  6. 6.
    Khalafyan, A.A., Yakuba, Yu.F., Temerdashev, Z.A., et al., Statistical-probability simulation of the organoleptic properties of grape wines, J. Anal. Chem., 2016, vol. 71, no. 11, pp. 1138–1144.CrossRefGoogle Scholar
  7. 7.
    Pohl, P., What do metals tell us about wine? Trends Anal. Chem., 2007, vol. 26, pp. 941–949.CrossRefGoogle Scholar
  8. 8.
    Yakuba, Yu.F., Temerdashev, Z.A., and Khalaf’yan, A.A., Application of ranging analysis to the quality assessment of wines on a nominal scale, J. Anal. Chem., 2016, vol. 71, no. 2, pp. 205–214.CrossRefGoogle Scholar
  9. 9.
    Giaccio, M. and Vicentini, A., Determination of the geographical origin of wines by means of the mineral content and the stable isotope ratios: a review, J. Commod. Sci., Technol. Qual., 2008, vol. 47, pp. 267–284.Google Scholar
  10. 10.
    Hopfer, H., Nelson, J., Collins, T.S., et al., The combined impact of vineyard origin and processing winery on the elemental profile of red wines, Food Chem., 2015, vol. 172, pp. 486–496.CrossRefGoogle Scholar
  11. 11.
    Khalafyan, A.A., Yakuba, Yu.F., and Temerdashev, Z.A., Application of table of congruences and correspondence analysis to comparative assessment of wine quality in rating scale, Zavod. Lab., Diagn. Mater., 2016, vol. 82, no. 2, pp. 66–71.Google Scholar
  12. 12.
    Khalafyan, A.A., Temerdashev, Z.A., Yakuba, Yu.F., and Gutuchkina, T.I., The use of multivariate analysis for the final evaluation of the results of expert assessments, Zavod. Lab., Diagn. Mater., 2016, vol. 82, no. 10, pp. 71–78.Google Scholar
  13. 13.
    Egorov, E.A., Guguchkina, T.I., Adzhiev, A.M., and Oseledtseva, I.V., Geograficheskie zony vin i natsional’nykh kon’yakov (brendi) vysokogo kachestva na yuge Rossii (Geographical Production Areas of High-Quality Wine and National Cognac (Brandy) in Southern of Russia), Krasnodar: Prosveshchenie-Yug, 2013.Google Scholar
  14. 14.
    Kaunova, A.A., Petrov, V.I., Tsiupko, T.G., et al., Identification of wine provenance by ICP-AES multielement analysis, J. Anal. Chem., 2013, vol. 68, no. 9, pp. 917–922.CrossRefGoogle Scholar
  15. 15.
    Khalafyan, A.A., Statistica 6. Matematicheskaya statistika s elementami teorii veroyatnostei (Statistica 6: Mathematical Statistics with Elements of Theory of Probability), Moscow: Binom, 2010.Google Scholar
  16. 16.
    StatSoft, Electronic textbook on statistics, 2012. http://www.statsoft.ru/home/textbook/default.htm. Accessed March 28, 2017.Google Scholar

Copyright information

© Pleiades Publishing, Inc. 2018

Authors and Affiliations

  • V. O. Titarenko
    • 1
  • A. A. Khalafyan
    • 1
  • Z. A. Temerdashev
    • 1
    Email author
  • A. A. Kaunova
    • 1
  • E. A. Ivanovets
    • 1
  1. 1.Kuban State UniversityKrasnodarRussia

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