Using UV-Vis spectroscopy for simultaneous geographical and varietal classification of tea infusions simulating a home-made tea cup

Food Chem. 2016 Feb 1:192:374-9. doi: 10.1016/j.foodchem.2015.07.022. Epub 2015 Jul 8.

Abstract

In this work we proposed a method to verify the differentiating characteristics of simple tea infusions prepared in boiling water alone (simulating a home-made tea cup), which represents the final product as ingested by the consumers. For this purpose we used UV-Vis spectroscopy and variable selection through the Successive Projections Algorithm associated with Linear Discriminant Analysis (SPA-LDA) for simultaneous classification of the teas according to their variety and geographic origin. For comparison, KNN, CART, SIMCA, PLS-DA and PCA-LDA were also used. SPA-LDA and PCA-LDA provided significantly better results for tea classification of the five studied classes (Argentinean green tea; Brazilian green tea; Argentinean black tea; Brazilian black tea; and Sri Lankan black tea). The proposed methodology provides a simpler, faster and more affordable classification of simple tea infusions, and can be used as an alternative approach to traditional tea quality evaluation as made by skilful tasters, which is evidently partial and cannot assess geographic origins.

Keywords: Classification; Geographical origin; Successive Projections Algorithm; Tea; UV–Vis spectroscopy; Variety.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Argentina
  • Brazil
  • Camellia sinensis / chemistry*
  • Camellia sinensis / growth & development
  • Discriminant Analysis
  • Food Inspection / methods*
  • Geography
  • Least-Squares Analysis
  • Principal Component Analysis
  • Spectrophotometry, Ultraviolet / methods*
  • Sri Lanka
  • Tea / chemistry*
  • Tea / classification*

Substances

  • Tea