Moët Hennessy, Analog Devices and UC Davis Test Chemical-Sensing System for Wine Quality

Moët Hennessy, Analog Devices (ADI) and the University of California, Davis, are working to apply chemical sensing and machine learning to viticulture and winemaking. The collaboration aims to detect chemical signatures from grapevines, juice and wine to give production teams earlier indications of biological processes and potential quality risks.

The partners report that their first application targets Fresh Mushroom Aroma (FMA), a wine quality risk. Researchers at Moët Hennessy’s Robert-Jean de Vogüé Research Center assembled samples and related data to train algorithms to recognize associated chemical signatures. The organizations say the system identified samples presenting elevated FMA risk before the defect would traditionally be detected.

The partners are also researching possible applications in early vine-disease detection, soil assessment and identifying other defects, including those they associate with climate-related events such as wildfires. They describe the system as a decision-support tool intended to complement the judgment of growers and winemakers.

ADI plans to make the technology available for other industrial applications. Moët Hennessy and UC Davis are exploring whether shared reference libraries could benefit the wider grape and wine industry.