Geographical identification of Chianti red wine based on ICP-MS element composition. (15th June 2020)

• Record Type: Journal Article
• Authors: Bronzi, Benedetta; Brilli, Claudio; Beone, Gian Maria.; Fontanella, Maria Chiara; Ballabio, Davide; Todeschini, Roberto; Consonni, Viviana; Grisoni, Francesca; Parri, Francesco; Buscema, Massimo
• Is Part Of: Food chemistry. Volume 315(2020)
• Publication Date: 2020-06-15
• Subjects: Major and trace elements -- REE -- ICP-MS -- Multivariate modelling -- PLS-DA -- Chianti wine; Food -- Analysis -- Periodicals; Food -- Composition -- Periodicals; 664
• DOI: 10.1016/j.foodchem.2020.126248
• Languages: English
• ISSNs: 0308-8146

Abstract

Highlights: Massive sampling of Chianti red wines, which are distinguished with a PDO label. Major, trace and Rare Earth elements were used as fingerprints for Chianti identification. Multivariate classification is able to discriminate Chianti and non-Chianti samples. Abstract: Chianti is a precious red wine and enjoys a high reputation for its high quality in the world wine market. Despite this, the production region is small and product needs efficient tools to protect its brands and prevent adulterations. In this sense, ICP-MS combined with chemometrics has demonstrated its usefulness in food authentication. In this study, Chianti/Chianti Classico, authentic wines from vineyard of Toscana region (Italy), together samples from 18 different geographical regions, were analyzed with the objective of differentiate them from other Italian wines. Partial Least Squares-Discriminant Analysis (PLS-DA) identified variables to discriminate wine geographical origin. Rare Earth Elements (REE), major and trace elements all contributed to the discrimination of Chianti samples. General model was not suited to distinguish PDO red wines from samples, with similar chemical fingerprints, collected in some regions. Specific classification models enhanced the capability of discrimination, emphasizing the discriminant role of some elements.