Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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Pattern Recognition for Typification of Whiskies and Brandies in the Volatile Components using Gas Chromatographic Data

  • Myoung, Sungmin (Dept. of Health Administration, Jungwon University) ;
  • Oh, Chang-Hwan (Dept. of Oriental Medical Food and Nutrition, Semyung University)
  • Received : 2016.02.19
  • Accepted : 2016.05.04
  • Published : 2016.05.31
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Abstract

The volatile component analysis of 82 commercialized liquors(44 samples of single malt whisky, 20 samples of blended whisky and 18 samples of brandy) was carried out by gas chromatography after liquid-liquid extraction with dichloromethane. Pattern recognition techniques such as principle component analysis(PCA), cluster analysis(CA), linear discriminant analysis(LDA) and partial least square discriminant analysis(PLSDA) were applied for the discrimination of different liquor categories. Classification rules were validated by considering sensitivity and specificity of each class. Both techniques, LDA and PLSDA, gave 100% sensitivity and specificity for all of the categories. These results suggested that the common characteristics and identities as typification of whiskies and brandys was founded by using multivariate data analysis method.

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References

  1. D. Gonzalez-Arjona, G. Lopez-Perez, V. Gonzalez-Gall ero and A. Gustavo, "Supervised pattern recognition procedures for discrimination of whisky from gas chromatography/mass spectrometry congener analysis" J. Agric. Food, Chem., Vol. 47, No. 2, pp. 20-46, Jun. 2014.
  2. C. Oh, B. Kim, S. Ahn and K. Kim, "Development of physicochemical methods for the characterization of adulterated foods" Food Science and Industry, Vol. 47, No. 2, pp. 20-46, Jun. 2014.
  3. Council Regulation, "(EEC) No. 1576/89" Off. J. Eur. Commun, pp.1-, 1989.
  4. D. Gonzalez-Arjona, V. Gonzalez-Gallero, F. Pablos and A. Gustavo, "Authentication and differentiation of irish whiskeys by higher-alcohol congener analysis" Analytica Chimica Acta, Vol. 381, No. 2, pp. 257-264, Mar 1999. https://doi.org/10.1016/S0003-2670(98)00764-8
  5. R. Aylott, A. Clyne, A. Fox and D. Walker, "Analytical strategies to confirm Scotch whisky authenticity" Analyst, Vol. 119, No. 8, pp. 1741-1746, Aug 1994. https://doi.org/10.1039/an9941901741
  6. J. Choi, K. Bang, K. Han and B. Noh, "Discrimination analysis of the geographical origin of foods" Korean J. Food Sci. Technol., Vol. 44, No. 5, pp. 503-525, May 2012. https://doi.org/10.9721/KJFST.2012.44.5.503
  7. B. Noh and D. Lee, "New product development by using principle component analysis" Food Sci. Indus., Vol. 29, pp. 2-12, Jan 2012.
  8. M. Berry and G. Linoff, "Data Mining techniques: For marketing, sales and customer relationship management" Wiley, New York, pp. 80-100, 2011.
  9. L. Wilson, J. Ding and A. Woods, "Gas chromatographic determination and pettern recognition analysis of methanol and fusel oil concentrations in whiskeys" J. Assoc. Off. Anal. Chem, Vol. 74, pp. 248-256, Mar 1991.
  10. J. Ledauphin, C. Le Milbeau, D. Barillier and D. Hennequin, "Differences in the volatile compositions of French labeled brandies(Armagnac, Calvados, Cognac, and Mirabelle) using GC-MS and PLS-DA" J. Agric. Food. Chem., Vol. 58, pp. 7782-7793, Sep 2010. https://doi.org/10.1021/jf9045667
  11. K. Varmuza and P. Filzmoser, "Introduction to Multivariate Statistical Analysis in Chemometrics" CRC Press, pp. 74-80, 2009.
  12. Y. Cho, S. Moon and K. Ryu, "Clustering analysis by customer feature based on SOM for predicting purchase pattern in recommendation system" Journal of the Korean Society of Computer and Information, Vol. 19, No. 2, pp. 193-200, Feb 2014.
  13. D. Massart and K. Leonard, "The interpretation of analytical chemical data by the use of cluster analysis" Wiley, pp. 15-40, 1983.
  14. B. Ripley, "Pattern recognition and neural networks" Cambridge University Press, pp. 150-178, 2007.
  15. K. Kim and M. Jeon, "Multivariate Statistical Data Analysis" Free Academy, pp. 213-221, 1999.
  16. S. Wold, M. Sjostrom and L. Eriksson, "PLS-Regr ession: a Basic Tool of Chemometrics" Chemometrics Intell. Lab. Syst., Vol. 58, pp. 109-130, Apr. 2014.
  17. I. Han, M. Kim, C. Lee, W. Cha, B. Ham, J. Jeong, H. Lee, C. Chung and C. Han, "Application of partial least squares method to a terephthalic acid manufacturing process for product quality control" Korean J. Chem. Eng., Vol. 20, pp. 977-984, Sep. 2003. https://doi.org/10.1007/BF02706925
  18. I. Han and H. Shin, "Modelling of a PEM fuel cell stack using partial least squares and artificial neural networks" Korean Chem. Eng. Res., Vol. 53, pp. 236-242, Feb. 2015. https://doi.org/10.9713/kcer.2015.53.2.236
  19. S. Kim, "Classification with categorical data using partial least squares" Sungkyunkwan University, pp. 8-9, 2011.
  20. I. Chong and C. Jun, "Performance of some variable selection methods when multicolinearity is present" Chemometrics Intell. Lab. Syst., Vol. 78, pp. 103-112, Jan. 2005. https://doi.org/10.1016/j.chemolab.2004.12.011
  21. D. Lee, H. Park, K. Kim, T. Lee and B. Noh, "Determination and Multivariate Analysis of Flavour Components in the Korean Folk Sojues Using GC-MS" Korean J. Food Sci. Technol., Vol. 26, pp. 750-758, Jun 1994.