{"api":{"host":"https:\/\/pinot.decanter.com","authorization":"Bearer YjY4NGEwYmE3YjliYWY2YzFjYzRiYzZiY2YwMTBjZDc2MGQ4MGYwZTliZjFiOGQ0OTlhOTMwMDMxMGNkYTdhZg","version":"2.0"},"piano":{"sandbox":"false","aid":"6qv8OniKQO","rid":"RJXC8OC","offerId":"OFPHMJWYB8UK","offerTemplateId":"OFPHMJWYB8UK","wcTemplateId":"OTOW5EUWVZ4B"}}

AI can pinpoint which estate Bordeaux wines come from with 100% accuracy

A machine learning algorithm has demonstrated the ability to identify the precise origin of Bordeaux wines by analysing their chemical makeup.

Researchers described the algorithm as a ‘100% reliable model’ that could be used to combat counterfeiting within the fine wine trade.

A team from the University of Geneva in Switzerland used artificial intelligence to assess the chemical composition of 80 red wines from seven different châteaux.

They used wines from 12 different vintages between 1990 and 2007, all from renowned estates in Bordeaux.

The researchers vaporised the wines and broke them down to chemical components, resulting in a readout for each wine. The readout is known as a chromatogram, and it has around 30,000 points representing separate chemical compounds.

The team then used 73 chromatograms to train the AI, along with data on the vintage and the estate that produced the wines.

Researchers then tested the algorithm on seven chromatograms that were held back to see if it could guess which estate had produced the wines.

It managed to do so with 100% accuracy. The researchers repeated the process 50 times, changing the wines used each time, and the algorithm consistently earned full marks.

‘Our results show that it is possible to identify the geographical origin of a wine with 100% accuracy, by applying dimensionality reduction techniques to gas chromatograms,’ said lead researcher Alexandre Pouget, a neuroscience professor at the University of Geneva.

His goal was to identify a specific, invariable chemical signature for each estate. ‘The wine sector has made numerous attempts to answer this question, with questionable or sometimes correct results, but involving heavy techniques.’

Co-author Stéphanie Marchand, a professor at the Institute of Vine and Wine Science at the University of Bordeaux, added: ‘This [study] allowed us to show that each estate does have its own chemical signature. We also observed that three wines were grouped together on the right and four on the left, which corresponds to the two banks of the Garonne on which these estates are located.’

The algorithm could now be used to nail down each estate’s terroir in a more scientific manner than was previously possible.

Pouget believes that it could also be used to fight back against fraud. ‘There’s a lot of wine fraud around, with people making up some crap in their garage, printing off labels, and selling it for thousands of dollars,’ he said. ‘We show for the first time that we have enough sensitivity with our chemical techniques to tell the difference.’

It is the latest in a long line of remarkable developments in the rapidly advancing world of artificial intelligence. Machine learning tools can now beat the world’s best chess players, pass the bar and diagnose diseases.

AI has also been deployed at wineries, which use algorithms to monitor harvests, predict yields, sort grapes, manage inventory and prevent spoilage.

Related articles

France kicks off plan to grub up nearly 9% of Bordeaux vineyard

Fresh clue to red wine headaches revealed by new study

Bordeaux 1982 revisited: 45 wines tasted

Latest Wine News