D-wines: use of LC-MS metabolomic space to discriminate italian mono-varietal red wines

Priorat and Montsant Appellations of Origin are located in the south of Catalonia (North‐East Spain), under severe Mediterranean climatic conditions

Press wines play a crucial role in red winemaking, representing up to 15% of the final blend [1]. Optimizing their value is essential both economically and for maintaining wine identity, especially given evolving climatic and societal challenges. However, little recent research exists on their composition.

this research investigates the impact of early oxygen exposure, also during malolactic fermentation (MLF), on pigments and color of a red wine from Sangiovese grapes

Forest fires in the vicinity of vineyards have significantly increased in the last decade and are a concern for grapegrowers and winemakers in many wine producing countries. The fires cause smoke drift throughout vineyards which cannot be avoided and may result in the production of wines described as ‘smoke tainted’. Such wines are characterized by undesirable sensory characters described as ‘smoky’, ‘burnt’, ‘ash’ aromas and flavours, and also may cause a lingering, unpleasant ashy aftertaste [1; 2].

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.