Impact of aging on dimethyl sulfide (DMS) in Corvina and Corvinone wines

Most oxidation reactions in wine require iron as a catalyst. The iron content of wine has decreased greatly in recent decades due to the use of low or no release cellar materials; however, in some cases it is still necessary to adopt winemaking practices to remove excess iron from wine, prevent its oxidation, and be able to reduce the addition of sulfur dioxide and other antioxidants.

The success of grafting in viticulture is deeply influenced by the nutrient composition of both rootstock and scion
materials. Key components such as nitrogen and carbohydrates play a crucial role in graft compatibility, establishment,
and overall plant vigor [1].

In addition to aroma compounds also protein composition strongly influences the quality of wines. Proteins of wine derive mainly from the plant Vitis vinifera and may be influenced by abiotic stress as well as fermentation conditions or fining. Additionally, fungal infections can affect the protein content as well by introducing fungal proteins or affecting grape protein composition. An infection of the vine with the plant pathogenic fungus Botrytis (B.) cinerea was shown to cause a degradation of proteins in the resulting wine. Moreover, it influences the foaming properties in sparkling wine.

The Northeast region of Brazil is characterized by a semi-arid climate, has produced tropical wines since twenty years ago. The region is located at 09º 09’ South, 40º 22’ West, 365.5 m

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