Recently, scientists have successfully developed aArtificial Intelligence Tools, through machine learning technology, is able to pass(grape) wineDifferences in the concentration of trace compounds in a wine can be accurately traced to its authenticity, even to specific vineyards and wineries.
The research team trained the program by using gas chromatography to chemically analyze 80 wines from seven different chateaux in the Bordeaux region of France over a 12-year period. Unlike traditional methods, the algorithm does not look for a single compound to differentiate the wines, but rather uses all the chemicals detected in the wine to determine the most reliable "chemical signature" of each wine. The program brings together wines with similar "chemical signatures" by displaying the results on a two-dimensional grid.
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The research shows that this method not only allows precise tracing to specific vineyards and wineries, but also reveals the unique "chemical notes" of each winery, rather than just a single molecule. The results of this research have significant applications not only for combating wine fraud, but also for monitoring the wine production process to ensure the quality of the wine and the equilibrium of the blends.
However, while the program is accurate up to 99% in tracing wines to the correct winery, there are challenges in distinguishing between vintages, theHighestOnly 50% is accurate. Nonetheless, the study, published in the journal Communication Chemistry, highlights the potential value of machine learning techniques in fraud investigations, particularly in the €2.6bn (£2.6bn) of sales lost in Europe each year due to counterfeit alcohol.
In addition to its obvious application in the fight against fraud, the head of the study said that this method could also be used to monitor the entire wine production process to ensure the quality of the blends. He noted that the use of such a tool would allow the production ofTopThe cost of wine is reduced, thus benefiting more people.