The social construction of wine-growing areas: the “Graves de Bordeaux”

Vineyards are complex agro-ecosystems with high spatial and temporal variability. An efficient training system may counteract the adverse effects of this variability. Moreover, considering the climate change issues, choosing an efficient training system that enhances water use and protects the vines from radiative thermal stress has become a priority for the farmers. A multidisciplinary approach that assesses the soil-crop-yield-wine relationships of vineyards in a distributed and holistic way could bring added knowledge on the behavior of the different training systems. This ongoing research aimed to implement a multidisciplinary approach to study the behavior of “Aglianico del Vulture” grapevines trained with two different systems: a spurred cordon (SC) and an “Alberello in parete” (AL), grown in a high-quality wine production area of Basilicata region (Italy). The approach merged several methods and scales of soil, ecophysiology, must/wine quality, and spectral data collection to assess the influence of the training system. Homogeneous zones (HZs) in both training systems were defined through a procedure based on geomorphological classification, unmanned aerial vehicles (UAV) images analysis, and a traditional soil survey supported by geophysical scanning. During the 2021 season, TDR probes monitored soil water content, while grapevine health status was assessed using eco-physiological measurements (LWP, chlorophyll content, PSII photosynthetic efficiency, LAI, and point-based field spectroscopy). These grapevine in-vivo measurements validated the spectral vegetation indexes (NDVI, RENDVI, CVI, and TVI) derived from the UAV multispectral imagery, which monitored the grapevine status in a distributed and non-invasive way. Grape yield, quality of berries, must and wine were measured to assess the effects of the training systems. The first experimental year results showed the variability of the vineyards and revealed relationships among soil parameters, crop characteristics, and vegetation indices of the SC and AL training systems. This multidisciplinary study could bring new insights into the vineyard training system’s effects on grape yield and wine quality.

The balance between the different flavours of a wine largely determines its perception and appreciation by the consumers. In white wines, sweetness and sourness are usually the two poles balancing the taste properties. The bitter flavour, on the other hand, is frequently associated with a loss of equilibrium and all white wines (dry and sweet, young and aged) are affected.
Several bitter compounds are already well-described in wines.

Nowadays, winemaking is dealing with great challenges, notably climate change, disease resistance and low pesticide inputs, desire for more sustainable agricultural productions and permanent changing of consumer preference.

Global warming due to greenhouse gases (GHG) has become a serious worldwide concern. The new EU green deal aims to achieve GHG emissions reduction by at least 55% by 2030 and a climate neutral eu economy by 2050. The deal strongly encourages GHG reducing measures at local, national and european levels. The redwine project will demonstrate the technical, economic and environmental feasibility of reducing by, at least, 31% of the CO2 eq.

The phenolic compounds of red wines represent a source of numerous benefits for human health, which is why they are a constant subject of scientific research. Winemaking in Serbia has a growing economic significance, with particularly autochthonous varieties included [1]. This research identifies and quantifies phenolic compounds of Serbian red varietal wines of Prokupac and Black Tamjanika varieties. Quantification of the level of phenolics has been conducted, including molecular tannins [(+)-catechin, (-)-epicatechin, procyanidin dimers B1, B2, B3, B4], molecular anthocyanins, and the mean degree of polymerization of tannins by HPLC by UV detection, total antioxidant capacity via spectrophotometric methods and chromatic characteristics via CIELAB.