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Updated: Nov 23, 2025

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Published on: November 8, 2019
Application of Ultraviolet-Visible Absorption Spectroscopy with Machine Learning Techniques for the Classification of
Aggelos Philippidis1, Emmanouil Poulakis1, Renate Kontzedaki1,2
1Institute of Electronic Structure and Laser, Foundation for Research and Technology-Hellas (IESL-FORTH), 700 13 Heraklion, Greece.
Abstract:
The present study was aimed at the identification, differentiation and characterization of red and white Cretan wines, which are described with Protected Geographical Indication (PGI), using ultraviolet-visible absorption spectroscopy. Specifically, the grape variety, the wine aging process and the role of barrel/container type were investigated. The combination of spectroscopic results with machine learning-based modelling demonstrated the use of absorption spectroscopy as a facile and low-cost technique in wine analysis. In this study, a clear discrimination among grape varieties was revealed. Moreover, a grouping of samples according to aging period and container type of maturation was accomplished, for the first time.
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