Multi-element Analysis and Geographical Origin Classification of Italian (Calabrian) Wines

Author(s): Francesco Caridi*, Maurizio D’Agostino, Alberto Belvedere, Antonio F. Mottese

Journal Name: Current Nutrition & Food Science

Volume 16 , Issue 8 , 2020

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Graphical Abstract:


Background and Objective: In this article, a comprehensive study was carried out for food authenticity evaluation through chemometric analyses, correlating botanical and geographical origins with food chemical composition.

Methods: A total of eighteen Calabrian red, rose and white wines were analyzed through Inductively Coupled Plasma Mass Spectrometry (ICP-MS).

Results: The mineral concentrations, determined by ICP-MS in the investigated wine samples, followed the subsequent order: K > P > Mg > Na > Ca > Fe > Cu > Zn > Mn > V.

The 2D Scatterplot and loading plot (Principal Component Analysis) showed that all red, rose and white wine samples from “Cirò” DOP area were grouped in the fourth, second and third quadrant, respectively, clearly separated from each other. Samples from “Cirò” red showed positive PC1 and were characterized by higher K, Fe, Mn, Na, V and Zn concentrations. Moreover, the points corresponding to two red wines from the “Terre di Cosenza” DOP area fall into the first quadrant; those corresponding to two rose wines from the “Donnici” and “Sant’Anna di Isola di Capo Rizzuto” DOP areas fall into the third and fourth quadrants, respectively; the point corresponding to a white wine from the “Donnici” DOP area falls into the second quadrant.

Conclusion: Experimental results demonstrated that it is possible to strictly relate, through the PCA, wines to their geographical and botanical provenance, thus becoming a useful tool for evaluating the product authenticity and guaranteeing it to the consumers.

Keywords: Chemometric analysis, geographical discrimination, ICP-MS, minerals, Principal Component Analysis (PCA), wines.

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Article Details

Year: 2020
Published on: 10 September, 2020
Page: [1259 - 1264]
Pages: 6
DOI: 10.2174/1573401316666200218140844
Price: $65

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