Targeted and untargeted 1H-NMR analysis for sparkling wine’s authenticity

Wildfires are becoming more common in many areas of the world that are also associated with wine grape production, especially the Pacific northwest United States, Australia and even some areas of France.

Historical records of grapevine phenology have been collected over decades throughout different winegrowing regions. These records have demonstrated advances in key developmental stages such as budburst, flowering and veraison because of increased temperatures due to climate change.

Light-struck taste (LST) is a wine fault that can occur in white and sparkling wines when exposed to light. This defect is mainly associated to the formation of methanethiol and dimethyl disulfide due to light-induced reactions involving riboflavin (RF) and methionine [1]. The presence of RF in wine is mainly due to the metabolism of yeast [2] which fermenting activity can be favoured by using yeast derivative products (YDPs) as nutrients. Nonetheless, a previous study showed the addition of YDPs before the alcoholic fermentation (AF) led to higher concentrations of RF in wines [3]. Due to the widespread use of YDPs in the winemaking process, this study aimed to understand the possible relation between the content of RF in wine and the YDP adopted as nutrient for AF.

Leaf removal in the bunch zone is a common viticultural practice with several objectives, yet it has been difficult to conclusively link the physiological mechanism(s) and metabolic berry impact to this widely practiced treatment. We used a field-omics approach1 in a Sauvignon blanc high altitude model vineyard, showing that the early leaf removal in the bunch zone caused quantifiable and stable responses (over years) in the microclimate where the main perturbation was increased exposure. We provide an explanation for how leaf removal leads to the shifts in grape metabolites typically linked to this treatment and confirm anecdotal evidence and previous reports that leaf removal treatment at an early stage of berry development affects “quality-associated” metabolites (monoterpenes and norisoprenoids).

Spatial variability of vine productivity in winegrapes is important to characterise as both yield and quality are relevant for the production of different wine styles and products. The objectives were to understand how patterns of variability of Cabernet Sauvignon fruit composition changed over time and space, how these patterns could be characterised with indirect measurements, and how spatial patterns of the variation in fruit compositional attributes can aid in improving management. Prior to the 2017 vintage, 125 data vines were distributed across each of four vineyards in the Lodi American Viticultural Area (AVA) of California. Each data vine was sampled at commercial harvest in 2017, 2018, and 2019. Yield components and fruit composition were measured at harvest for each data vine, and maps of yield and fruit composition were produced for eight ‘objective measures of fruit quality’: total anthocyanins, polymeric tannins, quercetin glycosides, malic acid, yeast assimilable nitrogen, β-damascenone, C6 alcohols and aldehydes, and 3-isobutyl-2-methoxypyrazine. Patterns of variation in anthocyanins and phenolic compounds were found to be most stable over time. Given this relative stability, management decisions focused on fruit quality could be based on zonal descriptions of anthocyanins or phenolics to increase profitability in some vineyards. In each vineyard, dormant season pruning weights and soil cores were collected at each location, elevation and soil apparent electrical conductivity surveys were completed, and remotely sensed imagery was captured by fixed wing aircraft and two satellite platforms at major phenological stages. The data collected were used to develop relationships among biophysical data, soil, imagery, and fruit composition. The standardised and aggregated samples from four vineyards over three seasons were included in the estimation of ‘common variograms’ to assess how this technique could aid growers in producing geostatistically rigorous maps of fruit composition variability without cumbersome, single season sampling efforts.