Selecting varieties best adapted to current and future climate conditions based on ripening traits

AIM Durello is a sparkling wine produced in the Lessini mountains near Verona. The wine is made from Durella grapes, a native white grape variety with a particularly high acidity. In spite of the small production area (375 ha for only 35 producers), there is a growing interest in this product. However, little is known about the aromatic profiles of these wines. The aim of this work was to characterize the aroma profile of Durella base wines suitable for the production of Lessini Durello sparkling wine. METHODS 14 base wines from Durella grapesfrom different producers were used for this study. Solid Phase Microextraction (SPME) and Solid Phase Extraction (SPE) sampling techniques coupled to GC-MS analysis allowed to identify and quantify a total of 62 volatile compounds. RESULTS Durello base wines showed relatively high levels of vitispirane, ß-damascenone, ß-citronellol and esters.

The introduction of ai-driven tools in digital content creation represents a significant shift in the landscape of marketing, particularly for industries reliant on rich visual storytelling such as the wine sector. The development of ai models like openai’s sora, runway’s gen-2 or google’s lumiere, which can generate realistic video content from textual descriptions, offers promising new avenues for enhancing brand narrative and consumer engagement. This research explores the potential of text-to-video (t2v) ai models to revolutionize wine marketing by creating dynamic, engaging content that captures the essence of vineyards and their products without the need for traditional video production processes.

In the course of this study, stabilisation (lees stirring in unclarified must) with skin contact and classic white wine vinification were compared for the Sauvignon blanc and Traminer varieties in Austria. The test wines were analysed for the volatile substances esters, free monoterpenes and fruity thiols

Climate change challenges differently wine growing systems, depending on their biophysical, sociological and economic features. Therefore, there is a need to locally design and evaluate adaptation strategies combining several technical options, and considering the local opportunities and constraints (e.g. water access, wine typicity). The case study took place in a typical and heterogeneous Mediterranean vineyard of 1,500 ha in the South of France. We developed a participatory modeling approach to (1) conceptualize local climate change issues and design spatially explicit adaptation strategies with stakeholders, (2) numerically evaluate their effects on phenology, yield and irrigation needs under the high-emissions climate change scenario RCP 8.5, and (3) collectively discuss simulation results. We organized five sets of workshops, with in-between modeling phases. A process-based model was developed that allowed to evaluate the effects of six technical options (late varieties, irrigation, water saving by reducing canopy size, adjusting cover cropping, reducing density, and shading) with various distributions in the watershed, as well as vineyard relocation. Overall, we co-designed three adaptation strategies. Delay harvest strategy with late varieties showed little effects on decreasing air temperature during ripening. Water constraint limitation strategy would compensate for production losses if disruptive adaptations (e.g. reduced density) were adopted, and more land got access to irrigation. Relocation strategy would foster high premium wine production in the constrained mountainous areas where grapevine is less impacted by climate change. This research shows that a spatial distribution of technical changes gives room for adaptation to climate change, and that the collaboration with local stakeholders is a key to the identification of relevant adaptation. Further research should explore the potential of adaptation strategies based on soil quality improvement and on water stress tolerant varieties.

Glutathione (L-g-glutamyl-L-cysteinyl-glycine) is a tripeptide which contains three constitutive amino acids: glutamate, cysteine and glycine. It is present in plants and foods, and fruits like grapes.