New fungus-resistant grapevine varieties display high and drought-independent thiol precursor levels

Oxidation in wine is mostly related to the Michael addition of nucleophiles on two quinones formed from the oxidation of ortho-diphenols. In wine this mechanism is responsible for the increase of the yellow hue and aroma loss. Glutathione exerts its antioxidant activity throughout its competitive addition onto quinones, but many other compounds can have the same behavior: sulfanyl
compounds, amino acids, etc. Addition of yeast derivates during the winemaking process can increase the level of those nucleophilic compounds and then confer to the wine a higher resistance

AIM: Grape withering is an oenological post-harvest process used for production of reinforced and sweet wines. Drying can be carried out by keeping the ripe grape in traditional large, well-aired rooms (non-controlled environment) or, more and more often, in a warehouse under controlled conditions of airflow and relative humidity (controlled environment)[1].

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.

Climate strongly affects the geographical distribution of grape varieties, grapevine cultivation techniques and wine organoleptic properties.

One of the major issues for wine production in Australia is the management and eradication of powdery and downy mildews and the associated yield losses they present, costing Australian grape growers upwards of AUD$160M per annum [1].