Leaf elemental composition in a replicated hybrid grape progeny grown in distinct climates

wo spectrophotometric methods are recommended by the Organisation Internationale de la vigne et du vin (OIV). The first is the method after Glories, were the absorbances at 420 nm, 520 nm and 620 nm are measured (OIV 2006a).

Late spring frost is a major challenge for various winegrowing regions across the world, its occurrence often leading to important yield losses and/or plant failure. Despite a significant increase in minimum temperatures worldwide, the spatial and temporal evolution of spring frost risk under a warmer climate remains largely uncertain. Recent projections of spring frost risk for viticulture in Europe throughout the 21st century show that its evolution strongly depends on the model approach used to simulate budburst. Furthermore, the frost damage modelling methods used in these projections are usually not assessed through comparison to field observations and/or frost damage reports.
The present study aims at comparing frost risk projections simulated using six spring frost models based on two approaches: a) models considering a fixed damage threshold after the predicted budburst date (e.g BRIN, Smoothed-Utah, Growing Degree Days, Fenovitis) and b) models considering a dynamic frost sensitivity threshold based on the predicted grapevine winter/spring dehardening process (e.g. Ferguson model). The capability of each model to simulate an actual frost event for the Vitis vinifera cv. Chadonnay B was previously assessed by comparing simulated cold thermal stress to reports of events with frost damage in Chablis, the northernmost winegrowing region of Burgundy. Models exhibited scores of κ > 0.65 when reproducing the frost/non-frost damage years and an accuracy ranging from 0.82 to 0.90.
Spring frost risk projections throughout the 21st century were performed for all winegrowing subregions of Bourgogne-Franche-Comté under two CMIP5 concentration pathways (4.5 and 8.5) using statistically downscaled 8×8 km daily air temperature and humidity of 13 climate models. Contrasting results with region-specific spring frost risk trends were observed. Three out of five models show a decrease in the frequency of frost years across the whole study area while the other two show an increase that is more or less pronounced depending on winegrowing subregion. Our findings indicate that the lack of accuracy in grapevine budburst and dehardening models makes climate projections of spring frost risk highly uncertain for grapevine cultivation regions.

The development of off-flavours in wine distillates, particularly those associated with the tails fraction, is a key issue in the production of high-quality spirits.

As the frequency and intensity of drought events increase, understanding the mechanisms of plant resilience to water deficit is crucial. To maintain an appropriate plant yield, a common practice is the application of high amounts of fertilizers with negative environmental impacts. The single and combined effect of water deficit and nutrient availability, namely nitrogen (N) and potassium (K), in Vitis Vinifera L. cv. Cabernet Sauvignon and Grenache was evaluated. Two-year-old grapevine plants grafted on SO4 rootstock were transferred in pots under semi-environmental conditions. During the growing season, plants were either maintained well-watered (100% ETc) or subjected to a controlled water deficit irrigation (33% ETc).

Wine is one of the most representative components of Mediterranean diet. Moderate wine intake together with food, has been positively correlated with reduced risk of many chronic diseases. This beneficial effect seems to be ascribed to elevated polyphenolic content of wine [1]. Traditional approaches for the identification of wine biomarkers consumption include targeted metabolomics that focuses on the quantification of well-defined metabolites, losing a valuable information about a massive number of compounds. On the other hand, untargeted metabolomics can disclose a large quantity of signals corresponding to potential biomarkers in a single analysis with high sensitivity and resolution.