To a better understanding of the impact of vine nitrogen status on volatile thiols from plot to transcriptome level

Saccharomyces cerevisiae (SC) is the main driver of alcoholic fermentation however, in wine, non-Saccharomyces species can have a powerful effect on aroma and flavor formation. This study aimed to compare untargeted volatile compound profiles from SPME-GC×GC-TOF-MS of Sauvignon blanc and Shiraz wine inoculated with six different non-Saccharomyces yeasts followed by SC. Torulaspora delbrueckii (TD), Lachancea thermotolerans (LT), Pichia kluyveri (PK) and Metschnikowia pulcherrima (MP) were commercial starter strains, while Candida zemplinina (CZ) and Kazachstania aerobia (KA), were isolated from wine grape environments. Each fermentation produced a distinct chemical profile that was unique for both grape musts. The SC-monoculture and CZ-SC sequential fermentations were the most distinctly different in the Sauvignon blanc while the LT-SC sequential fermentations were the most different from the control in the Shiraz fermentations.

Green cover in vine rows provides many ecological services, but can also negatively impact the crop, depending on the weed species. The composition of a vineyard weed community is influenced by many parameters. Ensuring an evolution of the vine row flora into a desired direction is therefore very complex. A key step towards this goal is to know which factors influence the establishment of the weed community and which types of communities are best suited for vineyards. In this study, we analysed the weed communities of several vineyards in the Lake Geneva region (379 botanical surveys on 117 plots), with the aim to highlight the links between soil management practices (chemical and mechanical weeding, mowing, mulching roll) and phytosociological profiles, biodiversity and selected functional traits (growth forms, life strategies, root depth). T

Comprehensive two-dimensional gas chromatography (GCxGC) has emerged as a powerful analytical technique for unraveling the volatile composition of complex matrices. This work will present three applications of GCxGC Tof-MS to the oenological field, aimed to identify novel biomarkers to be used in the quality control process of the wine industry. Comprehensive mapping of volatile compounds was conducted in a large sample of 70 sparkling wines, produced by 48 different wineries across 6 vintages and representative of the two main production areas for premium Italian sparkling wines (Franciacorta (FC) and Trentodoc (TN)), using HS-SPME followed by GCxGC-Tof-MS and multivariate analysis. Selection and identification of 196 putative biomarkers allowed clear separation of sparkling wines from FC and TN.

Around the world, the alcohol content of wine has been steadily increasing; partly as a consequence of climate change, but also due to improvements in viticultural management practices and winemaking techniques [1,2]. Concurrently, market demand for wines with lower alcohol levels has increased as consumers seek to reduce alcohol intake for social and/or health reasons [3]. As such, there is increasing demand for both innovative methods that allow winemakers to produce ‘reduced alcohol wines’ (RAW) and a better understanding of the impact of such methods on the composition of RAW. This study therefore aimed to investigate compositional changes in two red wines resulting from partial alcohol removal following treatment by one such method, involving a combination of reverse osmosis and evaporative perstraction (RO-EP).

1,1,6-trimethyl-1,2-dihydronaphtelene (TDN) evokes the odor of “petrol” in wine, especially in the variety Riesling. Increasing UV-radiation due to climate change intensifies formation of carotenoids in the berry skins and an increase of TDN-precursors1. Exploring new viticultural and oenological strategies to limit TDN formation in the future requires precise knowledge of TDN thresholds in different matrices. Thresholds reported in the literature vary substantially between 2 µg/L up to 20 µg/L2,3,4 due to the use of different methods. As Riesling grapes are used for very different wine styles such as dry, sweet or sparkling wines, it is essential to study the impact of varying ethanol and carbonation levels.