Use of the soils information system for detailed vineyard soil surveys and as a component of precision viticulture

Volatile organic compounds (VOCs) are very important for the characterisation and quality of the final white wine. An oenological practice to increase the extraction of aroma compounds is the cold pre-fermentative maceration [1,2], although it may also release phenolic compounds that confer darker chromatic traits to white wines, not appreciated by consumers. This practice could be improved by the use of enzymes in order to facilitate the release of the odorous molecules. In this study, the effect of different enzyme treatments during skin contact on the chromatic characteristics and volatile composition of white musts from four winegrape varieties was evaluated.

The influence of two pre-veraison and post-veraison regulated deficit irrigation (RDI) strategies on yield and grape quality was analyzed during a two year period for mature grapevines (cv. Monastrell) in Southeastern of Spain

Precision viticulture aims to optimize vineyard management by monitoring and responding to variability within vine plots. this work presents a comprehensive study on the application of hyperspectral imaging (hsi) technology for monitoring purposes in precision viticulture. authors explore the deployment of hsi sensors on various platforms including laboratory settings, terrestrial vehicles, and unmanned aerial vehicles, facilitating the collection of high-resolution data across extensive vineyard areas.

In the Burgundy vineyard, frequent tractor traffic and management of inter-rows alternating grass cover and chemical weed-control lead to structural soil contrast between row and inter-row. The aim of this study was to characterize and model water flow in relation with topsoil structure modifications induced by these practices. Void ratio of the different soil volumes were determined using bulk density measurements.

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: