Novel approaches and promising perspectives for enhancing grapevine editing and regeneration

Acetaldehyde is a volatile carbonyl compound synthetized by yeast during alcoholic fermentation, but it can also be formed by oxidation of ethanol during wine aging [1]. At low concentration, it enhances the fruity aroma, however, at higher levels, it can generate the appearance of notes of bruised and rotten apple [2]. From a chemical point of view, acetaldehyde is a reactive low-

Row orientation and canopy management are essential for high quality grapevine production. Microclimatic conditions of the leaves and fruits can be influenced by the canopy geometry. Remote sensing is a very promising tool to describe vegetative growth and physiological behavior of vineyards. However, the correlation between remotely sensed data and in situ field measurements has been described scarcely in the scientific literature so far. The aim of the study was to correlate remotely sensed data obtained with Unmanned Aerial Vehicle (UAV) with in situ field measurements to describe canopy structure.

Performing accurate vineyard yield estimation is of upmost importance as it provides important benefits to the whole vine and wine industry. Recently, image-analysis approaches have been explored to address this issue however this approach has as main challenge the bunch occlusion, mostly by vegetation but also by neighboring bunches. The present work aims at assessing the magnitude of bunch occlusion by neighboring bunches and to evaluate its dependency on a selection of vegetative and reproductive vine parameters assessed at fruiting zone. Forty vine segments (1 m) of two vineyard plots of the white cultivars ‘Alvarinho’ and ‘Arinto’ were assessed for vegetative and reproductive features at fruiting zone and imaged with a 2D camera.

Among the macromolecules of enological interest in white wines, much attention has been paid to polysaccharides.

Current climate change is increasing inter- and intra-annual variability in atmospheric conditions leading to grapevine phenological shifts as well altered grape ripening and composition at ripeness. This study aims to (i) detect weather anomalies within a long-term time series, (ii) model grape ripening revealing altered traits in time to target specific ripeness thresholds for four Vitis vinifera cultivars, and (iii) establish empirical relationships between ripening and weather anomalies with forecasting purposes. The Day of the Year (DOY) to reach specific grape ripeness targets was determined from time series of sugar concentrations, total acidity and pH collected from a private company in the period 2009-2021 in North-Eastern Italy. Non-linear models for the DOY to reach the specified ripeness thresholds were assessed for model efficiency (EF) and error of prediction (RMSE) in four grapevine cultivars (Merlot, Cabernet Sauvignon, Glera and Garganega). For each vintage and cultivar, advances or delays in DOY to target specified ripeness thresholds were assessed with respect to the average ripening dynamics. Long-term meteorological series monitored at ground weather station by means of hourly air temperature and rainfall data were analyzed. Climate statistics were obtained and for each time period (month, bimester, quarter and year) weather anomalies were identified. A linear regression analysis was performed to assess a possible correlation that may exist between ripening and weather anomalies. For each cultivar, ripeness advances or delays expressed in number of days to target the specific ripening threshold were assessed in relation to registered weather anomalies and the specific reference time period in the vintage. Precipitation of the warmest month and spring quarter are key to understanding the effect of climate change on sugar ripeness. Minimum temperatures of May-June bimester and maximum temperatures of spring quarter best correlate with altered total acidity evolution and pH increment during the ripening process, respectively.