Chemical activation of ABA signaling in grapevine through ABA receptor agonists

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:

Microbial ecosystems are primary drivers of viticultural, oenological and other cellar-related processes
such as wastewater treatment. Metagenomic datasets have broadly mapped the vast microbial species
diversity of many of the relevant ecological niches within the broader wine environment, from vineyard
soils to plants and grapes to fermentation. The data highlight that species identities and diversity
significantly impact agronomic performance of vineyards as well as wine quality, but the complexity
of these systems and of microbial growth dynamics has defeated attempts to offer actionable
tools to guide or predict specific outcomes of ecosystem-based interventions.

Aims: This work aimed i) to calibrate the accuracy of estimating vineyard water status by crop water stress index (CWSI) compared to stem water potential; ii) to determine the time interval during the day that best correlates to stem water potential and iii) to understand the its usefulness.

Beihong and Beimei were bred as winemaking cultivars released by Institute of Botany, the Chinese Academy of Sciences in 2008. The cultivars are selected from the population of ‘Muscat Hamburg’ (Vitis vinifera) ×V. amurensis. They are extended to most provinces in North of China because they have strong resistance to cold and disease and need not be buried in soil in winter. To better understand the effect of cropload on volatile compounds during wine-making, we surveyed volatiles composition and content of different cropload level in 3-years-old ‘Beihong’ and ‘Beimei’ vines which planted in east foot of Helan mountain of Ningxia (EHN).

Trebbiano di Lugana (TdL) is a white variety of Vitis vinifera mainly cultivated in an Italian area located south near Garda lake (Verona, north of Italy). This grape cultivar, also known as “Turbiana,” is used for the production of TdL wine with recognized Protected Designation of Origin whose volatile profile was recently determined [1]. The presence of varietal thiols in TdL, namely 3-mercaptohexan-1-ol and its acetate form, conferring the tropical and citrus notes, has been documented. Winemaking strategies were also described with the purpose of protecting and maintain these desired aromas [2]. To the best of our knowledge, the varietal thiol precursors (VTPs) were not previously determined in TdL grape and must. This study aimed to quantify VTPs in both grape during the ripening and must during the pressing. Volatile C6 compounds were also measured in the must fractions.