Enhancing plant defense: carbon dots for efficient spray-induced gene silencing 

Grapevine rootstocks play a pivotal role in influencing scion vigor, yield, and fruit quality, making their selection critical for sustainable vineyard management.

The aim of the project was to characterize the Premium Denomination of Guaranteed Origin (DOCG) “Colline Teramane” wine-growing region and to delineate and define homogeneous zones (terroir units) within it, by applying a multivariate clustering approach combined with geomatics.

In the current context of market competition and consumption evolution, it is necessary to produce wines of a genuine typicity. The Terroir represents an unique and irreproducible inheritance that can be valorized through the origin and the sensory characteristics of the wines.

Conflicting messages about the consumption of alcoholic beverages – including wine – continue to dominate the media, causing increasing uncertainty among consumers and health professionals.

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