Cell-to-cell contact modulates Starmerella bacillaris early death in mixed fermentations with Saccharomyces cerevisiae in a couple-dependent way

The consequences of the global climate change in the vitiviniculture are revealed as a gap between phenolic and technological grape maturities, higher grape sugar concentration that leads to high wine alcohols levels, lower acidities and high pH values, among others. The unbalanced phenolic maturity caused in this scenario leads to harsh astringency and to instable colour of wines. Previous studies have reported that the addition of yeast mannoproteins (MPs) to wines may have positive effects on these two organoleptic properties due to their capability to interact with wine polyphenols [1]; however, studies about the effect of the pH on these interactions have not been carried out so far.

Aim: The aim of this work was to evaluate the use of Variable Rate Application technologies based on prescription maps in commercial vineyards with large intra-parcel variability to achieve a more sustainable distribution of Plant Protection Products (PPP)

Nitrogen (N) nutrition of the vineyard strongly influences the must and the wine compositions. Several chemical markers present in wine (i.e., proline, succinic acid, higher alcohols and phenolic compounds) have been proposed for the cultivar Chasselas, as indicators of N deficiency in the grape must at harvest [1]. Grape genetics potentially influences the impact of N deficiency on grape composition, as well as on the concentration of potential indicators in the wine. The goal of this study was to evaluate if the che- mical markers found in Chasselas wine can be extended for other white wines to indicate N deficiency in the grape must.

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:

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