A mechanistic investigation of H/D scrambling processes in flavonoids

Production, demand, and brand awareness of dealcoholized wine (<0.5% v/v) is steadily increasing worldwide. However, there have been few studies to date investigating and comparing the different physical processes for dealcoholizing wine.

Quercetin (Q) is present in grape in form of glycosides and as aglycone. These compounds are extracted from grape skins during winemaking. In wines, following the hydrolysis reactions, the amount of quercetin aglycon can exceed its solubility value. Unfortunately, a threshold solubility concentration for quercetin in wine is not easy to determine because it depends on wine matrix (Gambuti et al., 2020).

Table grapes, being consumed as fresh, raisins, and transformed products are among the most appreciated fruits worldwide. Its popularity is increasing also due to its organoleptic and nutritional qualities that meet the consumers’ interest in healthier foods. Recent data from International Organization of Vine and Wine (OIV) revealed that table grape production has doubled in the last twenty years, and varietal availability has increased thanks to the several breeding programs.
To maintain the socio-economic impact of this sector, new challenges need to be addressed.

Under the pressure of global warming, several wine grape growing regions around the world are increasingly suffering from advanced and compressed phenology; endangering wine character while also creating serious logistic problems. From a physiological standpoint, the issue of delaying ripening is not simple as, in several instances, only a few processes must be delayed (i.e. sugar accumulation into the berries) while other events such as pigmentation and accumulation of other important phenolic compounds should proceed at a normal rate. Thus, the issue of decoupling technological maturity from phenolic maturity is another important consideration. Over the last decades, several research groups have endeavored to establish alternate cultural practices aimed at addressing this decoupling. In some cases, special applications of quite robust and well known practices regarding physiological principles have been utilized, however some completely new techniques are also being studied. In figure 1 of the review, we offer a panorama of the available tools and in the text we elaborate on those having provided most reliable and consistent results under an array of genotypes and environmental conditions. Among these, primary focus is given to post‐veraison—apical to the cluster—leaf removal (that can also be suitably replaced by applications of anti‐transpirants); the use of kaolin against multiple summers’ stresses; and a drastic version of late winter pruning having the potential to postpone ripening into a cooler period with improved grape composition and a limited negative impact on yield and storage reserves replenishment. 

Currently, the main goal of agriculture is to promote the resilience of agricultural systems in a sustainable way through the improvement of use efficiency of farm resources, increasing crop yield and quality under climate change conditions. This last is expected to drastically modify plant growth, with possible negative effects, especially in arid and semi-arid regions of Europe on the viticultural sector. In this context, the monitoring of spatial behavior of grapevine during the growing season represents an opportunity to improve the plant management, winegrowers’ incomes, and to preserve the environmental health, but it has additional costs for the farmer. Nowadays, UAS equipped with a VIS-NIR multispectral camera (blue, green, red, red-edge, and NIR) represents a good and relatively cheap solution to assess plant status spatial information (by means of a limited set of spectral vegetation indices), representing important support in precision agriculture management during the growing season. While differences between UAS-based multispectral imagery and point-based spectroscopy are well discussed in the literature, their impact on plant status estimation by vegetation indices is not completely investigated in depth. The aim of this study was to assess the performance level of UAS-based multispectral (5 bands across 450-800nm spectral region with a spatial resolution of 5cm) imagery, reconstructed high-resolution satellite (Sentinel-2A) multispectral imagery (13 bands across 400-2500 nm with spatial resolution of <2 m) through Convolutional Neural Network (CNN) approach, and point-based field spectroscopy (collecting 600 wavelengths across 400-1000 nm spectral region with a surface footprint of 1-2 cm) in a plant status estimation application, and then, using Bayesian regularization artificial neural network for leaf chlorophyll content (LCC) and plant water status (LWP) prediction. The test site is a Greco vineyard of southern Italy, where detailed and precise records on soil and atmosphere systems, in-vivo plant monitoring of eco-physiological parameters have been conducted.