Application of fuzzy algorithms in conjunction with 1H‐NMR spectroscopy to differentiate alcoholic beverages

Background Recent statistics from the European Commission indicate that wine is one of the commodities most commonly subject to food fraud. In this context, the development of reliable classification models to differentiate alcoholic beverages requires, besides sensitive analytical tools, the use of...

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Bibliographic Details
Published in:	Journal of the science of food and agriculture Vol. 103; no. 4; pp. 1727 - 1735
Main Authors:	Pirnau, Adrian, Feher, Ioana, Sârbu, Costel, Hategan, Ariana Raluca, Guyon, Francois, Magdas, Dana Alina
Format:	Journal Article
Language:	English
Published:	Chichester, UK John Wiley & Sons, Ltd 15.03.2023 John Wiley and Sons, Limited
Subjects:	1H‐NMR agriculture Alcoholic beverages Algorithms Artificial intelligence Beverages Classification Cultivars Differentiation Discriminant analysis Distillates food fraud Fraud fruit spirits Fruits fuzzy algorithms Geographical distribution Magnetic resonance spectroscopy Metabolomics NMR NMR spectroscopy Nuclear magnetic resonance nuclear magnetic resonance spectroscopy principal component analysis Principal components analysis spectral analysis Spectroscopy Spectrum analysis Statistical analysis Statistics Wine Wines
ISSN:	0022-5142, 1097-0010
Online Access:	Get full text
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