Authenticating the geographical origin of wine using fluorescence spectroscopy and machine learning and qNMR metabolomics as a tool for wine authenticity

David Jeffery, of The University of Adelaide, had the opportunity to present the work of one of his PhD students “Authenticating the geographical origin of wine using fluorescence spectroscopy and machine learning”. The choice of utilizing spectroscopic methods was made as they are attractive, they can be rapid, cost-effective and simple. They identified fluorescence spectroscopy, and more specifically, the collection of an excitation-emission matrix (EEM) that acts like a molecular fingerprint. Multivariate statistical modelling was then used in conjunction with the EEM data to develop classification models for wines from various regions. They developed such a technique, using a relatively new type of machine learning algorithm known as extreme gradient boosting discriminant analysis. This unique approach, which can routinely achieve a level of accuracy of 100% in comparison to ICP-MS at an average of 85%, is being applied to a range of studies on Shiraz and Cabernet Sauvignon wines from different regions of Australia.

In the second video, Inès Le Mao, of the Université de Bordeaux presents her research project “qNMR metabolomics a tool for wine authenticity and winemaking processes discrimination”. qNMR Metabolomic applied to wine offers many possibilities. The first application that is increasingly being studied is the authentication of wines through environmental factors such as geographical origin, grape variety or vintage. Another less common approach is from a qualitative point of view by studying the various oenological practices used that are an integral part of the elaboration of a wine. At UBx they wondered whether quantitative NMR could be used to dissociate the physical or chemical processes commonly used in oenology. The objective of this work was to provide a better understanding of the interactions between oenological processes and wine by determining the metabolites responsible for differentiation through 1H-NMR fingerprinting and chemometrics.

Videos of the entries submitted to the Enoforum Web Contest 2021 during the Enoforum Web Conference (23-25 February 2021)

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