Assessing bunch architecture for grapevine yield forecasting by image analysis 

Phenolic compounds are fundamental to wine quality, influencing its colour, mouthfeel, stability, and ageing potential [1]. Their extraction and evolution during fermentation plays a crucial role in determining the final sensory attributes and requires careful monitoring to guide winemaking decisions.

Grape (Vitis vinifera) is one of the world’s oldest agricultural fruit crops, grown for wine, table grape, raisin, and other products. One of the factors that can cause a reduction in the grape growing area is temperature rise due to climate change. Elevated temperature causes changes in grapevine phenology and fruit chemical composition. Previous studies showed that grape varieties respond differently to a temperature shift of 1.5°C; few varieties had difficulties in the fruit development or could not reach the desired Brix level.

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:

Different “landscape unit” have been identified in Bolgheri area (a viticultural appellation in the Tirrenian coast of Tuscany) by the aid of pedological, landscape and agronomic observations in the 1992-1993 period. In all cultivar (Sangiovese, Cabernet Sauvignon and Merlot) x landscape unit combinations, experimental plots were chosen in homogeneous vineyards, single cordon trained (about 3300-4500 vines/hectare). Grape maturation was studied by weekly samples of berries from veraison to vintage in the 1992-1995 period. At harvest yield and must composition traits were measured and, from the most représentative plots, sixty kilograms of grapes were harvested each year and vinified according to a standardised scheme. Wines were evaluated by standard chemical and sensory analyses.

Under standard champagne tasting conditions, the complex interplay between the level of dissolved CO2 found in champagne, its temperature, the glass shape, and the bubbling rate, definitely impacts champagne tasting by modifying the neuro-physico-chemical mechanisms responsible for aroma release and flavor perception. Based on theoretical principles combining heterogeneous bubble nucleation, ascending bubble dynamics and mass transfer equations, a global model is proposed (depending on various parameters of both the wine and the glass itself), which quantitatively provides the progressive losses of dissolved CO2 from laser-etched champagne glasses.