4.6 Article

Classification and authentication of tea according to their geographical origin based on FT-IR fingerprinting using pattern recognition methods

Journal

JOURNAL OF FOOD COMPOSITION AND ANALYSIS
Volume 106, Issue -, Pages -

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jfca.2021.104321

Keywords

Authenticity; FT-IR spectral fingerprint; Classification; Linear discriminant analysis; Tea; Geographical origin

Funding

  1. University of Zanjan
  2. University of Vigo
  3. Universidade de Vigo/CISUG

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The potential of FT-IR spectra in classifying tea samples based on geographical origins was examined. Different pattern recognition methods, including PCA, PCA-LDA and PLS-DA, were investigated to achieve discrimination of tea samples. The results demonstrated that FT-IR spectral fingerprinting combined with pattern recognition methods can be employed as an effective and feasible method for classification of Iranian tea based on their geographical origins.
The potential of FT-IR spectra was examined to classify tea samples based on the geographical origins. Principal component analysis (PCA), principal component analysis-linear discriminant analysis (PCA-LDA) and partial least square-discriminant analysis (PLS-DA) were investigated in order to achieve discrimination of tea samples. Several spectral pre-processing methods, such as mean centering (MC), auto-scaling, multiplicative scatter correction (MSC), standard normal variate (SNV) and their combinations, were employed to improve the quality of the spectra. The results showed that the tea samples from five geographical regions can be identified based on using FT-IR spectral fingerprints. The results demonstrated that FT-IR spectral fingerprinting combined with pattern recognition methods can be employed as an effective and feasible method for classification of Iranian tea based on their geographical origins.

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