Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/131630
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dc.contributor.authorRanaweera, R.K.R.-
dc.contributor.authorCapone, D.L.-
dc.contributor.authorBastian, S.E.P.-
dc.contributor.authorCozzolino, D.-
dc.contributor.authorJeffery, D.W.-
dc.date.issued2021-
dc.identifier.citationMolecules, 2021; 26(14):4334-1-4334-15-
dc.identifier.issn1420-3049-
dc.identifier.issn1420-3049-
dc.identifier.urihttp://hdl.handle.net/2440/131630-
dc.descriptionPublished: 17 July 2021-
dc.description.abstractIn a global context where trading of wines involves considerable economic value, the requirement to guarantee wine authenticity can never be underestimated. With the ever-increasing advancements in analytical platforms, research into spectroscopic methods is thriving as they offer a powerful tool for rapid wine authentication. In particular, spectroscopic techniques have been identified as a user-friendly and economical alternative to traditional analyses involving more complex instrumentation that may not readily be deployable in an industry setting. Chemometrics plays an indispensable role in the interpretation and modelling of spectral data and is frequently used in conjunction with spectroscopy for sample classification. Considering the variety of available techniques under the banner of spectroscopy, this review aims to provide an update on the most popular spectroscopic approaches and chemometric data analysis procedures that are applicable to wine authentication.-
dc.description.statementofresponsibilityRanaweera K. R. Ranaweera, Dimitra L. Capone, Susan E. P. Bastian, Daniel Cozzolino and David W. Jeffery-
dc.language.isoen-
dc.publisherMDPI AG-
dc.rightsCopyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).-
dc.subjectauthenticity-
dc.subjectmultivariate analysis-
dc.subjectwine fingerprinting-
dc.subjectspectral data-
dc.subjectmachine learning-
dc.titleA review of wine authentication using spectroscopic approaches in combination with chemometrics-
dc.typeJournal article-
dc.identifier.doi10.3390/molecules26144334-
dc.relation.granthttp://purl.org/au-research/grants/arc/IC170100008-
pubs.publication-statusPublished-
dc.identifier.orcidRanaweera, R.K.R. [0000-0003-0578-3457]-
dc.identifier.orcidCapone, D.L. [0000-0003-4424-0746]-
dc.identifier.orcidBastian, S.E.P. [0000-0002-8790-2044]-
dc.identifier.orcidJeffery, D.W. [0000-0002-7054-0374]-
Appears in Collections:Agriculture, Food and Wine publications
ARC Training Centre for Innovative Wine Production publications
Aurora harvest 8

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