Postharvest ozone treatment in grapevine white cultivars: Effects on grape volatile composition

Inter-row soil tillage in vineyards, stimulates vigor and production due to the absence of competition for water and nutrients, however negatively affects organic matter content, soil erosion, and compaction, resulting in reduced fertility. In this study, we investigated the effects of different cover crop management approaches, including cultivation type and termination timing, on the physiological and productive responses of a Glera vineyard. The experimental trial was conducted in Precenicco (UD) from 2019 to 2021. A commercial mixture for autumn cover cropping was sown in alternating rows, and the sowing pattern was changed each year.

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.

Black rot, caused by Phyllosticta ampelicida (Guignardia bidwellii), is a serious fungal disease in viticulture. Incidences increased in recent years due to reduced pesticide treatments, neglected phytosanitary measurements, and effects of climate change.

Wine production is expanding in Scandinavia with a focus on organic growing, and Solaris becoming the signature grape of the region.

Flavescence dorée, a serious threat to grapevine cultivation in several European Countries, is caused by phytoplasmas in the 16Sr-V ribosomal group, classified as quarantine organisms in the EU and transmitted mainly by the insect vector Scaphoideus titanus. The disease is controlled only by indirect and preventive measures, with important economic and environmental concerns. Genetic resources from the great variety of Vitis vinifera germplasm together with application of new genomic techniques could be applied to produce resistant/tolerant plants, once the genetic bases of susceptibility are elucidated. In a current Italian project (BIORES*) we are evaluating different international and local grapevine cvs. as well as microvine plants for their response to FD transmission and multiplication in controlled conditions.