A DNA-free editing approach to help viticulture sustainability: dual editing of DMR6-1 and DMR6-2 enhances resistance to downy mildew 

Grape Phylloxera (Daktulosphaira vitifoliae Fitch) ordinarily has great difficulty establishing leaf galls on the European Grapevine (VitisviniferaL.). Yet populations of leaf-feeding Phylloxera are increasingly being observed throughout commercial vineyards world-wide. Effective plant protection strategies including quarantine actions are currently missing to fight, grape phylloxera populations in affected vineyards and combat linked negative effects on vines and yield. Contrary to the otherwise mandatory continuous infestation pressure from externally established populations (e.g. from populations developed on rootstock foliage or other interspecific hybrids, these leaf-feeding populations seem to establish themselves annually.

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

Many volatile compounds of different chemical/biochemical origin contribute to wine aroma. Certain key ‘varietal’ aroma compounds such as methoxypyrazines are formed in the grape and appear to be only scarcely influenced by fermentation.

Knowledge of vine reaction to plant spacing under high potential soil conditions is restricted. This study was done to determine effects of vine spacing

Wine quality maintenance during the storage is a fundamental aspect for both wine producers and consumers. Nowadays, great attention has been given to the light effect