Characterisation of tequila according to their major volatile composition using multilayer perceptron neural networks

Food Chem. 2013 Feb 15;136(3-4):1309-15. doi: 10.1016/j.foodchem.2012.09.048. Epub 2012 Sep 20.

Abstract

Differentiation of silver, gold, aged and extra-aged tequila using 1-propanol, ethyl acetate, 2-methyl-1-propanol, 3-methyl-1-butanol and 2-methyl-1-butanol and furan derivatives like 5-(hydroxymethyl)-2-furaldehyde and 2-furaldehyde has been carried out. The content of 1-propanol, ethyl acetate, 2-methyl-1-propanol, 3-methyl-1-butanol and 2-methyl-1-butanol was determined by means of head space solid phase microextraction gas chromatography mass-spectrometry. 5-(Hydroxymethyl)-2-furaldehyde and 2-furaldehyde were determined by high performance liquid chromatography with diode array detection. Kruskal-Wallis test was used to highlight significant differences between types of tequila. Principal component analysis was applied as visualisation technique. Linear discriminant analysis and multilayer perceptron artificial neural networks were used to construct classification models. The best classification performance was obtained when multilayer perceptron model was applied.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Alcoholic Beverages / analysis*
  • Discriminant Analysis
  • Gas Chromatography-Mass Spectrometry
  • Neural Networks, Computer
  • Solid Phase Microextraction
  • Volatile Organic Compounds / chemistry*

Substances

  • Volatile Organic Compounds