Tea types classification with data fusion of UV–Vis, synchronous fluorescence and NIR spectroscopies and chemometric analysis

Anna Dankowska , Wojciech Kowalewski

Abstract

The potential of selected spectroscopicmethods - UV–Vis, synchronous fluorescence andNIR aswell a data fusion of themeasurements by these methods - for the classification of tea sampleswith respect to the production process was examined. Four classification methods - Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Regularized Discriminant Analysis (RDA) and Support Vector Machine (SVM) -were used to analyze spectroscopic data. PCA analysis was applied prior to classification methods to reducemultidimensionality of the data. Classification error rateswere used to evaluate the performance of thesemethods in the classification of tea samples. The results indicate that black, green,white, yellow, dark, and oolong teas,which are produced by differentmethods, are characterized by different UV–Vis, fluorescence, and NIR spectra. The lowest error rates in the calibration and validation data sets for individual spectroscopies and data fusionmodelswere obtained with the use of the QDA and SVM methods, and did not exceed 3.3% and 0.0%, respectively. The lowest classification error rates in the validation data sets for individual spectroscopies were obtained with the use of RDA (12,8%), SVM(6,7%), and QDA (2,7%), for the UV–Vis, SF, and NIR spectroscopies, respectively.NIR spectroscopy combined with QDA outperformed other individual spectroscopic methods. Very low classification errors in the validation data sets - below3% -were obtained for all the data fusion data sets (SF+UV–Vis, SF+NIR, NIR+UV–Vis combined with the SVM method). The results show that UV–Vis, fluorescence and near infrared spectroscopies may complement each other, giving lower errors for the classification of tea types.
Author Anna Dankowska (WT / KTAS)
Anna Dankowska,,
- Department of Food Commodity Science
, Wojciech Kowalewski - Adam Mickiewicz University (UAM)
Wojciech Kowalewski,,
-
Journal seriesSpectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, [Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy], ISSN 1386-1425, (N/A 100 pkt)
Issue year2019
Vol211
Pages195-202
Publication size in sheets0.5
Keywords in Polishzafałszowania, herbata, metody spektroskopowe, metody chemometryczne, metody klasyfikacyjne
Keywords in Englishadulteration, tea, spectroscopic methods, chemoemtic methods, classifcation methods
ASJC Classification1602 Analytical Chemistry; 1607 Spectroscopy; 3105 Instrumentation; 3107 Atomic and Molecular Physics, and Optics
DOIDOI:10.1016/j.saa.2018.11.063
URL https://www.sciencedirect.com/science/article/abs/pii/S1386142518310606
Languageen angielski
Score (nominal)100
Score sourcejournalList
ScoreMinisterial score = 100.0, 15-04-2020, ArticleFromJournal
Publication indicators WoS Citations = 1; Scopus SNIP (Source Normalised Impact per Paper): 2017 = 1.104; WoS Impact Factor: 2018 = 2.931 (2) - 2018=2.665 (5)
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