Characterization of variety-specific changes in bulk stomatal conductance in response to changes in atmospheric demand and drought stress

Le régime thermique en période de maturation du raisin est l’une des variables déterminantes de la coloration du raisin et de la richesse en arômes, anthocyanes et polyphénols des vins.

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.

The frequency of bushfires close to wine regions around the world has increased in the last two decades. The economic losses incurred when grapes and wines are discarded due to ‘smoke taint’ are substantial (i.e., hundreds of millions of dollars). Efforts to mitigate and ameliorate smoke taint are therefore crucial. Chardonnay, rosé and cabernet sauvignon wines made from grapes exposed to smoke during the 2020 wildfires in eastern Australia were subjected to various amelioration techniques: the addition of activated carbons, molecularly imprinted polymers (mips), and a proprietary resin (either directly, or following membrane filtration); spinning cone column (scc) distillation; and finally, transformation into vinegar.

AIM: Vitamins are essential compounds to numerous organisms, including yeasts, and appear highly significant during winemaking processes.

INTEGRAPE was a European interdisciplinary network for “data integration to maximize the power of omics for grapevine improvement” (CA17111, https://integrape.eu/), funded by the European COST Association from September 2018 to 2022. This Action successfully developed guidelines and tools for data management and promoted the best practices in grapevine omics studies with a holistic future vision of: “Imagine having all data on grapevine accessible in a single place”.