From genes to vineyards: system biology and new breeding technologies for water stress tolerance in grapevines

1,1,6-Trimethyl-1,2-dihydronaphthalene (TDN) is a controversial aroma component found in Riesling wines. It belongs to the family of C13-norisoprenoids and is mainly associated with kerosene/petrol notes. TDN can add complexity to the wine aroma at medium – low concentrations and deteriorate the wine bouquet when its content is high. No TDN aromas are usually perceived in young Riesling wines, but they can appear after several years of aging due to the gradual formation of TDN. Management of TDN in Riesling wines is an actual task, since global warming can promote formation of this compound and compromise the aromatic composition of wine. Therefore, the aim of the current work was, firstly, to study the sensory particularities of TDN in Riesling wine at various concentrations. Secondly, to investigate the ability of bottle closures to absorb (scalp) TDN from Riesling wine under various storage conditions. These studies also include the comparative assessment of our findings with previously published data. METHODS: sensory analysis, GC-MS (SBSE), HPLC,1H-NMR and other methods related to the synthesis and determination of TDN. RESULTS: First of all, the method of the synthesis of highly purified TDN (95% and 99.5%) was optimized [1].

In the province of Frosinone from 1850 they are cultivated in some zones wine grape of French origin like Merlot, Cabernet franc Cabernet sauvignon, Sirah, Pinot noir. The insertion of these varieties was the work of Pasquale Visocchi in the great company of family “Fratelli Visocchi Proprietari” (F. V.P.).

Astringency is a crucial sensory attribute typically described as the drying and/or puckering sensation occurring after the consumption of tannin-rich foods and beverages. In this study, thirty-seven red wines from different varieties, origins and styles were evaluated, analyzing both chemical and sensory features. Principal Component Analysis was used for dimensionality-reduction and for correlating selected chemical parameters against astringency. The results showed that tannin content was the most important chemical parameter influencing overall astringency but more clearly the dryness sub-quality, followed by pH, titratable acidity and alcohol content.

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

Multiple Factor Analysis (MFA) According to the Chenin blanc Association of South Africa, there are three recognized dry wine styles, Fresh and Fruity (FF), Rich and Ripe Unwooded (RRU), and Rich and Ripe Wooded (RRW), classically attributed with the help of sensory evaluation. One of the “rapid methods” has drawn our attention for the purpose of simplifying and making style attribution for large sample sets, evaluated during different sessions, more robust. Polarized Projective Mapping (PPM) is a hybrid of Projective Mapping (PM) and Polarised Sensory Positioning (PSP). It is a reference-based method in which poles
(references) are used for the evaluation of similarities and dissimilarities between samples.