<sup>13</sup>C NMR-Based Chemical Fingerprint for the Varietal and Geographical Discrimination of Wines

<sup>13</sup>C NMR-Based Chemical Fingerprint for the Varietal and Geographical Discrimination of Wines

A fast, economic, and eco-friendly methodology for the wine variety and geographical origin differentiation using <sup>13</sup>C nuclear magnetic resonance (NMR) data in combination with machine learning was developed. Wine samples of different grape varieties cultivated in different reg...

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Bibliographic Details
Main Authors: Alberto Mannu, Ioannis K. Karabagias, Maria Enrica Di Pietro, Salvatore Baldino, Vassilios K. Karabagias, Anastasia V. Badeka
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Foods
Subjects:
wine
<sup>13</sup>C NMR fingerprint
MANOVA
factor analysis
<i>k</i>-nearest neighbors
partial least squares-discriminant analysis
Online Access:https://www.mdpi.com/2304-8158/9/8/1040

Internet

https://www.mdpi.com/2304-8158/9/8/1040

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