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  • 标题:Application of Ultraviolet-Visible Absorption Spectroscopy with Machine Learning Techniques for the Classification of Cretan Wines
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  • 作者:Aggelos Philippidis ; Emmanouil Poulakis ; Renate Kontzedaki
  • 期刊名称:Foods
  • 电子版ISSN:2304-8158
  • 出版年度:2021
  • 卷号:10
  • 期号:1
  • 页码:9
  • DOI:10.3390/foods10010009
  • 出版社:MDPI Publishing
  • 摘要: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.
  • 关键词:wine discrimination; grape varieties; wine maturation; aging; container; oak barrel; acacia barrel; Greek wines; Cretan wines; machine learning; multivariate analysis; chemometrics; OPLS-DA; ultraviolet–visible spectroscopy; spectral analysis wine discrimination ; grape varieties ; wine maturation ; aging ; container ; oak barrel ; acacia barrel ; Greek wines ; Cretan wines ; machine learning ; multivariate analysis ; chemometrics ; OPLS-DA ; ultraviolet–visible spectroscopy ; spectral analysis
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