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Predicting Bordeaux red wine origins and vintages from raw gas chromatograms

Food Science and Technology

Predicting Bordeaux red wine origins and vintages from raw gas chromatograms

M. Schartner, J. M. Beck, et al.

This intriguing study reveals how gas chromatography and mass spectrometry can unveil the hidden origins and vintages of Bordeaux red wines. Conducted by a team of remarkable researchers including Michael Schartner and Jeff M. Beck, the findings suggest that the chemical identity of wine is a complex mosaic rather than just a few key ingredients.... show more
Abstract
Connecting chemical properties to various wine characteristics is of great interest to the science of olfaction as well as the wine industry. We explored whether Bordeaux wine chemical identities and vintages (harvest year) can be inferred from a common and affordable chemical analysis, namely, a combination of gas chromatography (GC) and electron ionization mass spectrometry. Using 12 vintages (within the 1990–2007 range) from 7 estates of the Bordeaux region, we report that, remarkably, nonlinear dimensionality reduction techniques applied to raw gas chromatograms recover the geography of the Bordeaux region. Using machine learning, we found that we can not only recover the estate perfectly from gas chromatograms, but also the vintage with up to 50% accuracy. Interestingly, we observed that the entire chromatogram is informative with respect to geographic location and age, thus suggesting that the chemical identity of a wine is not defined by just a few molecules but is distributed over a large chemical spectrum. This study demonstrates the remarkable potential of GC analysis to explore fundamental questions about the origin and age of wine.
Publisher
Communications Chemistry
Published On
Dec 05, 2023
Authors
Michael Schartner, Jeff M. Beck, Justine Laboyrie, Laurent Riquier, Stephanie Marchand, Alexandre Pouget
Tags
Bordeaux red wines
gas chromatography
mass spectrometry
vintage prediction
machine learning
chemical identity
dimensionality reduction
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