Typologie des paysages de vigne: un outil de planification

The growing demand for renewable energy and sustainable agricultural practices has highlighted the potential of agrivoltaics (Agri-PV) as a promising solution, particularly in the context of German viticulture.

Investigating vineyard floor management is essential as these practices directly impact soil health, vine growth, and grape quality.

Climate change is likely to impact wine typicity across the globe, raising concerns in wine regions historically renowned for the quality of their terroir. Amongst several changes in viticultural practices, replacing some of the planting material (i.e clones, rootstocks and cultivars) is thought to be one of the most promising potential levers to be used for adapting to climate change. But the change of cultivars also involves the issue of protecting the region’s wine typicity.

The addition of fungal chitosan in wine is allowed since 2009 to release some spoilage microorganisms such as Brettanomyces bruxellensis (OIV/OENO 338A/2009; EC 53/2011). This yeast is able to produce volatil phenols and is responsible of organoleptic deviations compromising quality and typicality of red wines [1]. Despite the fact that fungal chitosan is highly renewable, no toxic and non-allergenic, its use remains marginal because this treatment is relatively recent (compare to sulphites treatment) and information are contradictory between different studies described in literature. For all these reasons,

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.