Structural composition of polymeric polyphenols of red wine after long-term ageing: effect of vinification technology

In Champagne, the vine adaptation to different climatic and technical changes during these last 20 years can be seen through physiological balance disruptions. These disruptions emphasize the general grapevine decline. Since the 2000s, among other nitrogen stress indicators, the must nitrogen has been decreasing. The combination of restricted mineral fertilizers and herbicide use, the growing variability of spring rainfall, the increasing thermal stress as well as the soil type heterogeneity are only a few underlying factors that trigger loss of physiological balance in the vineyards. It is important to weigh and quantify the impact of these factors on the vine. In order to do so, the Comité Champagne uses two key-tools: networking and modelization. The use of quantitative and harmonized ecophysiological indicators is necessary, especially in large spatial scales such as the Champagne appellation. A working group with different professional structures of Champagne has been launched by the Comité Champagne in order to create a common ecophysiology protocol and thus monitor the vine physiology, yearly, around 100 plots, with various cultural practices and types of soil. The use of crop modelling to follow the vine physiological balance within different pedoclimatic conditions enables to understand the present balance but also predict the possible disruptions to come in future climatic scenarios. The physiological references created each year through the working group, benefit the calibration of the STICS model used in Champagne. In return, the model delivers ecophysiology indicators, on a daily scale and can be used on very different types of soils. This study will present the bottom-up method used to give accurate information on the impacts of soil, climate and cultural practices on vine physiology.

In wine producing regions around the world, climate change has the potential to decrease the frequency and amount of precipitation and increase average and extreme temperatures. This will lower soil water availability and increase evaporative demand, thereby increasing the frequency and intensity of water deficit experienced in vineyards. Among other things, grapevines manage water deficit by regulating stomatal closure. The dynamics of this regulation, however, have not been well characterized across the range of Vitis vinifera cultivars. Providing a method to understand how different cultivars regulate their stomata, and hence water use in response to changes in soil water deficits will help growers manage vineyards and select plant material to better meet quality and yield objectives in a changing climate.

In the current viticultural context, global warming leads to advanced and possibly accelerated ripening which can alter the balance among desirable grape quality traits sought for winemaking. Evaluation of genetic material that displays delayed and/or slower ripening could uncover a potential “slow ripening” trait for incorporation into commercial varieties through breeding. In this study, we evaluated a white-fruited selection discovered in the Grape Breeding and Genetics program at E. & J. Gallo Winery that displayed an unusual ripening pattern compared to standard varieties. Vines of the slow-ripening selection did not differ in their visual appearance, water status or gas exchange characteristics compared to vines of its normal-ripening sibling.

Brazil has a recent history on geographical indications and product regulation for high quality wines. The first geographic indication implemented was the Vale dos Vinhedos Indication of Procedence (

To face emerging competition and challenges, wine producers globally rely on precision viticulture (PV) solutions to boost productivity, enhance quality, increase profitability, and reduce the environmental impact of vineyards. Current pv methods predominantly use multispectral sensor data from several platforms (satellites or vineyard installations). However, these applications generally use data analysis strategies lacking physiological grapevine support.