Moët Hennessy Tests AI System for Early Wine Defect Detection

Moët Hennessy, Analog Devices, Inc. and UC Davis have demonstrated an AI system that detects chemical signatures linked to wine quality risks, the organizations said in a press release. The system analyzes volatile compounds emitted by grapevines, juice and wine.

Its first application identified samples with an elevated risk of developing Fresh Mushroom Aroma before the defect could be detected through conventional methods. Researchers at Moët Hennessy's research center built a library of samples and related data to train machine learning algorithms to recognize the associated chemical patterns.

The platform combines sensing technology from Analog Devices with machine learning that identifies relevant signals across complex chemical data. The organizations are also researching its use for detecting vine diseases, assessing soil and identifying defects associated with events such as wildfires.