Mechanisms responsible for different susceptibility of grapevine varieties to flavescence dorée

Rotundone accumulation and biosynthesis is a complicated process. Previous research highlighted that these phenomenons were affected under ecophysiological conditions by viticultural practices (e.g. defoliation or irrigation). Individually, these practices often impact several abiotic factors that are difficult to separate such as temperature, water or nitrogen status, or radiation. Such dissociation can be achieved under controlled environmental conditions using potted vines.

Double cropping is a novel technique, driven by the extension of the growing season caused by global warming.

According to the last IPCC report, the scale of recent climate changes are unprecedented over many centuries. Each of the last four decades has been successively warmer than any decade since 1850. Projections for the future foresee that temperature could reach +3.3°C to +5.7°C under the most pessimistic scenario. It is also projected that every region will face more concurrent and multiple changes in climatic impact-drivers. The frequency of extreme climate events is also likely to increase, as well as the occurrence of indirect constraints. These evolving climatic conditions are alrealdy affecting and will continue to affect the suitability of traditional wine grape production areas, but also create opportunities in new locations.

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.

This study aims at exploiting an undervalued winemaking by-product, wine yeast lees, by developing efficient and food-grade methods for the extraction of yeast glycoproteins. These extracts were then supplemented to wine and their impact on wine properties assessed.