Leaf necrosis induced by the insecticide carbaryl in Vitis rupestris ‘B38’

In this study for the first time, eight natural stilbenes (trans-resveratrol, trans-piceid, cis-piceid, trans-astringin, trans-piceatannol, (+)-trans-s-viniferin, pallidol and hopeaphenol) isolated and purified from Vitis vinifera, were simultaneously separated and analysed within 5 mn by ultra high pressure liquid chromatography coupled with photodiode array detection.

Over the last decades, wine analysis has become an important analytical field, with emphasis placed on the development of new methodologies for characterization and elaboration control.

Light is responsible for adverse reactions in wine including the formation of unpleasant flavors, loss of vitamins or photodegradation of anthocyanins. Among them, the riboflavin degradation leads to the formation of undesirable volatile compounds, known as light-struck taste. These photo-chemical reactions could be avoided by simply using opaque packaging. However, most rosé wines are kept in transparent bottles due to different commercial reasons. Some agri-food waste extracts have been studied for their photoprotective action which turn to be highly correlated with phenolic content [1].

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.

Grape quality is a complex trait that mainly refers to berry chemical composition, including sugars, organic acids, phenolics, aroma and aroma precursor compounds.