Moët Hennessy, ADI, UC Davis flag wine defect early with AI

The effort brings together three very different players: Moët Hennessy, the wine and spirits division of LVMH; Analog Devices, a semiconductor company whose Health Solutions unit works on AI-driven sensing; and UC Davis, long recognized in viticulture and enology. The technology traces back to early research at the Massachusetts Institute of Technology, which Analog Devices has continued to develop for analyzing chemical signatures across many applications.

The first public result targets Fresh Mushroom Aroma, a defect the partners describe as one of the wine industry's most complex quality challenges. Researchers at Moët Hennessy's Robert-Jean de Vogüé Research Center assembled a library of samples and data to train machine learning algorithms on the chemical signatures tied to that risk, and the system then flagged elevated-risk samples earlier than conventional detection would.

Beyond that single defect, the organizations frame the platform as one for analyzing living systems generally, with research under way into early detection of vine diseases, soil assessment, and other defects, particularly those linked to climate change and events such as wildfires. Analog Devices intends to make the technology broadly available for future industrial applications, while Moët Hennessy and UC Davis are exploring how shared reference libraries could benefit the wider grape and wine industry — so how far the benefits spread beyond these partners is likely to depend on that openness.