Tools for assessing vine nitrogen status; role of nitrogen uptake in the “terroir” effect

Several trunk diseases cause decline and premature dieback of grapevines. In vineyards, these pathogens gain entry into plants through unprotected wounds. Wounds are also frequently infected during the propagation stages. The pathogens survive in infected plants in a latent form and cause disease in older grapevines or in plants that are

The search for underground shelters is one of the oldest forms of human habitation, providing refuge in extreme environments such as deserts and polar regions.

Developments in high-throughput sequencing (HTS) technologies allow us to obtain large amounts of microbial information from wine and must samples. Thus approaches, that are aimed at characterising the microbial diversity during fermentation, can be enhanced, or possibly even replaced, with HTS-based metabarcoding. To reduce experimental biases and increase data reproducibility, we compared 3 DNA extraction methods by evaluating differences in the fungal diversity with Riesling alcoholic fermentation samples at four different vineyards. The fungal diversity profiling was done using the genetic markers ITS2 and D2 using metabarcoding. The extraction methods compared consisted of a commercial kit, a recently published protocol that includes a DNA enhancer, and a protocol based on a buffer containing common inhibitor removal reagents. All methods were able to distinguish vineyard effects on the fungal diversity, but the results differed quantitatively.

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