Influenza delle componenti climatiche e pedologiche sulla variabilità dei contenuti polifenolici in alcuni ambienti vitati della DOCG Sagrantino di Montefalco

Combined improvements in sequencing technologies and assembly algorithms have led to staggering improvements in the quality of grape genome assemblies.

Located in the western bekaa region of lebanon, rachaya is known for its extensive history of viticulture and ideal mediterranean conditions for grapevine cultivation. Despite the area’s importance in grapevine production, there is limited knowledge about the local grape varieties grown there. In this work, we conducted a detailed analysis of five local grapevine varieties in the area, obeidy, kassoufi, foddeh, aswadi, and maryami, of which little is currently known, in comparison to a set of international varieties.

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

Over the past two years, the AWRI has received 69 wine samples suspected of being affected by mousy off-flavour. The character has been mostly observed in white wines.