Nuove soluzioni e strumenti per l’agricoltura e la viticoltura di precisione

Most vineyards are grafted and include a variety (Vitis vinifera) grafted over a wild Vitis rootstock (hybrids of V. berlandieri, riparia and rupestris). Grape berry quality at harvest depends on a subtle balance between acidity and the concentrations of sugars, polyphenols and precursors of aroma compounds. The mechanisms controlling the balance of sugars/acids/polyphenols are influenced by the abiotic environment, in particular nitrogen supply, and interact with the genotypes of both the scion variety and the rootstock. Previous work suggests that some of the effects of water stress are in fact linked to a nitrogen deficiency driven indirectly by the reduction of water absorption.

The present study evaluates the effect of prefermentative maceration enzymes and yeast autolysate on the concentration of conjugated precursors and volatile thiols, respectively.Sauvignon blanc and Merlot grapes underwent skin-contact maceration with or without pectolytic enzymes, for the production of white and rosé wines

In red wines, anthocyanins evolve during the wine-making process and ageing. They react with other compounds (such as vinylphenols, acetaldehyde, pyruvic acid…) to form a stable family of compounds called pyranoanthocyanins. Furthermore, the oxidation process can modify the anthocyanic profile of a red wine. It is also interesting to evaluate the occurrence of the different subclasses of pyranoanthocyanins and to characterize their chemical properties. The first objective of this study is to evaluate the occurrence of the different groups of pyranoanthocyanins in an oxidised Merlot wine by a centrifugal partition chromatography strategy. The second goal is to evaluate their relative impact in red wines from Bordeaux region by measuring their concentrations.

Global warming and increased frequency and/or severity of drought events are among the most threatening consequences of climate change for agricultural crops. In response to drought, grapevine (as many other plants) exhibits osmotic adjustment through active accumulation of osmolytes which in turn shift the leaf turgor loss point (TLP) to more negative values, allowing to maintain stomata opened at lower water potentials1. We investigated the capacity of Pinot noir leaves to modulate their osmotic potential as a function of: (i) time (seasonal osmoregulation), (ii) growing temperatures, and (iii) drought events, to enhance comprehension of the resilience of grapevines in drought conditions. We performed trails under semi-controlled field conditions, and in two different greenhouse chambers (20/15 °C vs 25/20 °C day/night). For two consecutive vegetative seasons, grafted potted grapevines (Pinot noir/SO4) were subjected to two different water regimes for at least 30 days: well-watered (WW) and water deficit (WD).

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.