Influence of nitrogen supply on colorimetric parameters of Lugana wines

The elemental composition (the ionome) of grape leaves is an important indicator of nutritional
health, but its genetic architecture has received limited scientific attention. In this study, we
analyzed the leaf ionome of 131 interspecific F1 hybrid progeny from a Vitis rupestris (♀) X Vitis
riparia (♂) cross. The progeny were replicated in New York, South Dakota, Southwest Missouri ad Central Missouri, and the concentration of 20 elements were measured in their leaves at
three different phenological stages during the growing season. In leaves collected at the apical node at anthesis, elemental concentrations correlated in a consistent manner (p < 0.05) across all four geographic locations. In subsequent phenological stages, elemental ratios in the apical-node leaves remained consistent across the South Dakota and New York sites, but not across the Missouri sites. In leaves collected at the basal and middle nodes, correlations varied greatly across all locations.

All about “Australian grapevine stories”

In interaction with climate and genetic or human factors, the soil is a major component of the viticulture terroir. The mineral composition of the soil influences vine performance and wine sensory attributes. Among the elements that vines take from the soil, nitrogen is the one that has the strongest impact on vine physiology, vigor and grape composition. In addition to its major effect on primary metabolites in berries, nitrogen plays also a decisive role in the secondary metabolism, especially in the production of key compounds for berries quality, like volatile thiols, methoxypyrazines and glutathione (GSH).

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:

The State Rio Grande do Sul is the main producer of Brazilian fine wines, with four viticultural regions. The objective is the characterization of the viticultural climatic potential of the State (total surface of 281.749 km2). The methodology use the Géoviticulture Multicriteria Climatic Classification System (Géoviticulture MCC System), based on three climatic indices – Dryness Index (DI), Heliotermal Index (HI) and Cool Night Index (CI).