Water status, nitrogen status and leaf area/ crop ratio effect on aromatic potential of vitis viniferaberries : example of Sauvignon blanc

Grapevine powdery mildew resistance is a key target for grape breeders and grape growers worldwide. The driver of the USDA-NIFA-SCRI VitisGen3 project is completing the pipeline from germplasm identification to QTL to candidate gene characterization to new cultivars to vineyards to consumers. This is a common thread across such projects internationally. We will discuss how our objectives and approaches leverage big data to advance this initiative, starting with genomics and computer vision phenotyping for gene discovery and genetic improvement. To manage and maintain resistances for long-term sustainability, growers will be trained through our nation-wide extension and outreach plan.

Context and purpose of the study ‐ The aim of this study is the examination of wines of 9 different clones of a Greek grape variety Xinomavro, (ΧE1, X19, X22, X28, ΧE2 X30, X31, X35, X36, X37), with regards to their phenolic and anthocyanin content and chemical composition.

In a previous zoning program (1998-2002), climatic and pedological factors were able to distinguish 14 terroir within the Soave DOC area where wine characteristics are well recognizable. Nevertheless, in the past vinegrowers identified several vineyards where a better quality of the grapes and wines could be obtained. So, « beyond the zonation » will aim to suggest a new methodology to characterise the Cru, starting with 15 vineyards that were selected in the Soave Classico DOC area. In the year 2005, a meteorological station was positioned in each vineyard and temperature data were collected; because of the limited area of investigation, only 3 rain sensors were set up.

Increasingly warm and dry climate conditions are challenging the viticulture and winemaking sector. Digital technologies and crop modelling bear the promise to provide practical answers to those challenges. As viticultural activities strongly depend on harvest date, its early prediction is particularly important, since the success of winemaking practices largely depends upon this key event, which should be based on an accurate and advanced plan of the annual cycle. Herein, we demonstrate the creation of modelling tools to assess grape ripeness, through sugar concentration monitoring. The study area, the Portuguese Côa valley wine region, represents an important terroir in the “Douro Superior” subregion. Two varieties (cv. Touriga Nacional and Touriga Franca) grown in five locations across the Côa Region were considered. Sugar accumulation in grapes, with concentrations between 170 and 230 g l-1, was used from 2014 to 2020 as an indicator of technological maturity conditioned by meteorological factors. The climatic time series were retrieved from the EU Copernicus Service, while sugar data were collected by a non-profit organization, ADVID, and by Sogrape, a leading wine company. The software for calibrating and validating this model framework was the Phenology Modeling Platform (PMP), version 5.5, using Sigmoid and growing degree-day (GDD) models for predictions. The performance was assessed through two metrics: Roots Mean Square Error (RMSE) and efficiency coefficient (EFF), while validation was undertaken using leave-one-out cross-validation. Our findings demonstrate that sugar content is mainly dependent on temperature and air humidity. The models achieved a performance of 0.65