Advances in the chemistry of rosé winemaking and ageing

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.

Terpenes are responsible for flavors and aromas of grapes, however, they also protect from radiation, participate in biotic stress and antioxidant mechanisms. The phytohormone methyl jasmonate (MeJA) mediates many of these stress responses and has been associated with increased terpene content in berries. Here, we generated transcriptomic data of Vitis vinifera cv. ‘Gamay’ cells treated with MeJA (100 μM) and cyclodextrins (50 μM) to understand these responses. Ontology analysis revealed that up-regulated genes (URGs) were enriched in jasmonic acid biosynthesis and signaling terms, as expected. Inspection of transcription factors (TFs) among URGs allowed us to study uncharacterized TFs.

In the current climatic context, with milder winters leading to earlier budburst in most wine regions, vines are exposed to the risk of spring frosts for a longer period. Depending on the year, frost can lead to yield losses of between 20 and 100 %, jeopardizing the economic survival of wine estates. In addition, by destroying young shoots, spring frosts can impact the following season’s production, by reducing the number of canes available for pruning, for example. Late pruning is one method to combat spring frosts.

Historically bounded by strict regulations with a focus on taxation since the 19th century, the japanese wine industry stands at a crossroads in the 21st century, necessitated by alignment with international standards and opening towards global markets.

In viticulture, the challenges of local climate modelling are multiple: taking into account the local environment, fine temporal and spatial scales, reliable time series of climate data, ease of implementation and reproducibility of the method. At the local scale, recent studies have demonstrated the contribution of spatialization methods for ground-based climate observation data considering topographic factors such as altitude, slope, aspect, and geographic coordinates (Le Roux et al, 2017; De Rességuier et al, 2020). However, these studies have shown questions in terms of the reproducibility and sustainability of this type of climate study. In this context, we evaluated the potential of MODIS thermal satellite images validated with ground-based climate data (Morin et al, 2020). Previous studies have been encouraging, but questions remain to be explored at the regional scale, particularly in the dynamics of the massive use of bioclimatic indices to classify the climate of wine regions. The results at the local scale were encouraging, but this approach was tested in the current study at the regional scale. Several objectives were set: 1) to evaluate the downscaling method for land surface temperature time series, 2) to identify regional thermal structure variations. We used weekly minimum and maximum surface temperature time series acquired by MODIS satellites at a spatial resolution of 1000 m and downscaled at 500 m using topographical variables. Two types of analyses were performed: