Abstract
The knowledge of a product’s origin is an important aspect for consumers who demand quality and authenticity. Grape juice is a beverage that has currently gained more attention due to the tendency of people towards a more natural and healthy lifestyle. The aim of this study was to discriminate the origin of grape juice samples. For this purpose, chemometric techniques were applied to commercial samples of grape juice from Argentina and Brazil, and the feasibility of classification models of predicting the origin of samples based on elemental composition, was investigated. Inductively coupled plasma mass spectrometry (ICP-MS) was used to determine 10 elements (V, Cr, Mn, Fe, Ni, Cu, As, Rb, Y and Mo). Unsupervised methods, such as principal component analysis (PCA) and cluster analysis (CA) and the supervised technique, linear discriminant analysis (LDA) with bootstrap** and k-fold cross-validation were assessed. The best result was achieved for LDA with 4 fold cross validation with a prediction accuracy of 81%.
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Acknowledgements
This work was supported by Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Agencia Nacional de Promoción Científica y Tecnológica (FONCYT) (Project PICT-2019-03859-BID) and Universidad Nacional de Cuyo (Project 06/M035-T1 (Argentina).
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Canizo, B.V., Diedrichs, A.L., Londonio, A. et al. Provenance discrimination of commercial grape juices from Argentina and Brazil based on elemental composition and chemometric methods. Food Measure 18, 2409–2419 (2024). https://doi.org/10.1007/s11694-024-02376-2
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DOI: https://doi.org/10.1007/s11694-024-02376-2