L’étude “terroirs d’Anjou”: un exemple de caractérisation intégrée des terroirs viticoles, utilisable à l’échelle parcellaire

The Institut Français De La Vigne Et Du Vin (IFV) is conducting many experiments on innovative winegrowing practices, which are emerging in companies in the sector, or which are still at the R&D stage for agricultural suppliers. The purpose of these practices may be to reduce environmental impact, to adapt vineyards to climate change, or to achieve other technical, economic or social aims. Whatever the objective, it is necessary to verify the relevance of these new practices, and in particular their environmental relevance, i.e. That at the very least, the changes in practices do not increase the environmental impact of the technical itineraries.

In this study we have compared the predictive ability of two phenological models: a traditional Thermal Time (TT) and a version of the more recently develop Unified Model (UM).

Wine lees are the sediment that settles at the bottom of wine barrels, tanks, or bottles during the winemaking process and represent the second most significant by-product of wineries.

Grapes are one of the world’s primary fruit crops, and pruning activities generate high amounts of annual wood wastes [1]. These pruning shoots contain valuable phenolic compounds and could have numerous potential applications [1,2]. Consequently, the aim of this work was to evaluate the physico-chemical properties of vine pruning residues with potential as enological additives. For this purpose, grapevine shoots from 12 varieties grown in Chile were collected during the winter of 2021.

Unmanned Aerial Vehicles (UAVs) are increasingly used to monitor canopy structure and vineyard performance. Compared with traditional remote sensing platforms (e.g. aircraft and satellite), UAVs offer a higher operational flexibility and can acquire ultra-high resolution images in formats such as true color red, green and blue (RGB) and multispectral. Using photogrammetry, 3D vineyard models and normalized difference vegetation index (NDVI) maps can be created from UAV images and used to study the structure and health of grapevine canopies. However, there is a lack of comparison between UAV-based images and ground-based measurements, such as leaf area index (LAI) and canopy porosity.