Moët Hennessy, Analog Devices and UC Davis test AI sensing for wine quality

Moët Hennessy, Analog Devices and UC Davis have formed a collaboration to apply ADI’s sensing and machine learning platform to viticulture and winemaking. The system analyzes volatile chemical signatures emitted by grapevines, juice and wine, using AI to identify signals linked to biological processes and emerging quality risks. The work builds on technology rooted in early research at MIT and is intended to provide earlier, more affordable insights than conventional testing methods.

The initial demonstration focused on Fresh Mushroom Aroma, one of the wine industry’s more complex quality challenges. Researchers at Moët Hennessy’s Robert-Jean de Vogüé Research Center built a sample and data library to train machine learning algorithms, enabling the technology to identify samples with elevated risk before the defect would traditionally be detected.

The partners see broader uses for the platform, including early detection of vine diseases, soil assessment and other defects linked to climate change events such as wildfires. The goal is to support researchers, viticulturists and winemakers with decision-support tools while preserving human expertise, craftsmanship and judgment in wine production.