Prediction of Fresh Mushroom Aroma (FMA) taint in must via volatile organic compound analysis

Abstract

Fresh Mushroom Aroma (FMA) is an undesirable off-flavor in wine, characterized by a button mushroom–like aroma. Reported in several French wine regions around 2000, FMA is associated with specific fungal consortia present on grapes. The defect is typically detected only at the end of alcoholic fermentation by sensory analysis. Early identification of FMA-risked musts would prevent economic losses associated with producing tainted wines and further prevent spoilage of wines via blending. Here, we report for the first time a technological approach enabling detection of FMA risk directly from grape must. The Signature Analysis Machine (SAM) is a tabletop electronic nose designed to analyze complex mixtures of volatile organic compounds (VOCs). VOC detection is achieved using a high-dimensional array of highly orthogonal sensors integrated into a vial cap, generating a distinctive multidimensional “signature” for each sample. Following supervised training on labeled datasets, SAM learns characteristic signatures associated with predefined classes and can subsequently classify unknown samples, with performance improving as additional data are acquired. SAM was trained using 26 FMA-tainted and 8 non-tainted Meunier musts, as well as 8 non-tainted pinot noir musts. Sensory evaluations and chemical analyses of the wines produced from these musts were used for validation. The model achieved 100 % specificity and greater than 90% sensitivity in detecting FMA taint directly from the original musts. Moreover, preliminary results indicate that SAM can predict the severity of FMA as later rated by trained sensory panels, weeks after fermentation, based solely on analysis of the initial must. These results demonstrate the potential of electronic-nose technology for early prediction of FMA in musts. Similar approaches are also being explored for smoke-taint detection in California, supporting the broader applicability of this strategy to vineyard-derived sensory risks.

References

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