Characterizing graft union formation in different scion/rootstock combinations of grapevine 

Irrigation initiation timing is a critical annual management decision that has cascading effects on grapevine productivity and wine quality.

The cultivated area of table grapes worldwide has experienced a paramount increase over the last two decades. In this current scenario, traditional varieties are being replaced by new cultivars that prioritize a profitable and sustainable agriculture, while satisfying consumer demands. It is widely recognized that wine varieties, especially those with red berry flesh, are renowned for their high antioxidant capacity and phenolic compounds, which promote health. Recently, this topic has also gained significance in table grape breeding programs.

The evolution of wine quality issues is historically expressed by the passage from wine quality (what is a wine?) to wine quality (what is a good wine?). Perhaps the next question could be: what is a good sustainable wine? To contribute to reflection on this theme, it may be worthwhile to undertake an exercise in prospective fiction, which we have identified in the hypothesis of the AOD, the “appellation d’origine durable”, a scenario we will develop in the light of developments in the wine industry and the regulation on geographical indications.

Depending on the variety, grapes contain several chemical classes of aromatic compounds (i.e., terpenols, norisoprenoids, benzenoids) mainly stored as glycosides in berry skin.

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.