AI is trained to identify fake wines; understand how

The researchers used machine learning to distinguish wines based on subtle differences in the concentrations of dozens of compounds, allowing them to trace wines not just to a specific grape-growing region, but to the winery where the wine was produced.

Researchers create AI tool with a nose for fraudulent wine https://t.co/OV5rNxDpoV

- Guardian news (@guardiannews) December 4, 2023

“There is a lot of wine fraud out there, with people inventing products in their garages, printing labels and selling them for thousands of dollars,” said the Prof. Alexandre Pouget, from the University of Geneva, Switzerland. “We have shown for the first time that we have enough sensitivity with our chemical techniques to distinguish the differences.”

How does the algorithm work?

To train the program, the scientists turned to gas chromatography, which had been used to analyze 80 wines harvested over 12 years from seven different properties in the Bordeaux region of France. This technique is commonly used in laboratories to separate and identify the compounds that make up a mixture.

Instead of trying to find individual compounds that differentiate one wine from another, the algorithm relies on all of the chemicals detected in the wine to determine the most reliable signature for each. The program displays your results in a two-dimensional grid, where wines with similar signatures are grouped together.

The research, which is due to be published in the journal Communications Chemistry, suggests that machine learning could aid fraud investigations by confirming whether wine matches the label.

While fraud detection is the most obvious application for the program, Pouget said the approach could be used to monitor quality throughout the winemaking process and ensure a good blend.

“We could use this to figure out how to blend wines to optimize quality,” he said.

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