The role of vine trunk height in delaying grape ripening: insights for viticultural adaptation strategies

The grapevine genome harbors considerable levels of structural variation that represent an important source of functional variation and could result in high levels of cis-regulatory variation.

Conserving and exploiting intra-varietal diversity in ancient grapevine varieties is essential to secure their future use whilst preserving the genetic heritage of historical winegrowing regions.

Dans la définition et la description d’un “territoire” (“terra” en italien), avec les facteurs du milieu et génétiques, un rôle important est joué par ceux agronomiques, techniques et de culture qui contribuent à caractériser le produit d’une zone spécifique.

Sparkling wine is defined as a wine containing carbon dioxide in solution, produced exclusively through a secondary fermentation process.

In viticulture, the challenges of local climate modelling are multiple: taking into account the local environment, fine temporal and spatial scales, reliable time series of climate data, ease of implementation and reproducibility of the method. At the local scale, recent studies have demonstrated the contribution of spatialization methods for ground-based climate observation data considering topographic factors such as altitude, slope, aspect, and geographic coordinates (Le Roux et al, 2017; De Rességuier et al, 2020). However, these studies have shown questions in terms of the reproducibility and sustainability of this type of climate study. In this context, we evaluated the potential of MODIS thermal satellite images validated with ground-based climate data (Morin et al, 2020). Previous studies have been encouraging, but questions remain to be explored at the regional scale, particularly in the dynamics of the massive use of bioclimatic indices to classify the climate of wine regions. The results at the local scale were encouraging, but this approach was tested in the current study at the regional scale. Several objectives were set: 1) to evaluate the downscaling method for land surface temperature time series, 2) to identify regional thermal structure variations. We used weekly minimum and maximum surface temperature time series acquired by MODIS satellites at a spatial resolution of 1000 m and downscaled at 500 m using topographical variables. Two types of analyses were performed: