Evaluation of the site index model for viticultural zoning

Oxidation in wine is mostly related to the Michael addition of nucleophiles on two quinones formed from the oxidation of ortho-diphenols. In wine this mechanism is responsible for the increase of the yellow hue and aroma loss. Glutathione exerts its antioxidant activity throughout its competitive addition onto quinones, but many other compounds can have the same behavior: sulfanyl
compounds, amino acids, etc. Addition of yeast derivates during the winemaking process can increase the level of those nucleophilic compounds and then confer to the wine a higher resistance

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.

Understanding vineyard site contribution to elemental composition of wines has, historically, been limited due to lack of continuity across multiple vintages, as well as lack of uniformity in scion clone and lack of controlled pilot-scale winemaking conditions.  We recently completed our fifth vintage, and have elemental composition characterizing wines from four vintages (2015–2018)

Brandy de Jerez (BJ) is a spirit drink made exclusively from spirits and wine distillates and is characterized by the use of casks for aging that previously contained Sherries. The quality and sensory complexity of BJ depend on the raw materials and some factors: grape variety, conditions during processing the wine and its distillation, as well as the aging in the cask. Therefore, the original compounds of the grapes from which it comes are of great interest being in most cases the Airén variety. Their relationship with the quality of the musts and the wines obtained from them has been studied (1) and varies each year of harvest depending on the weather conditions (2).

In the course of the present work, which is the first part of a study on the “characterization of Barbera dell’Oltrepo Pavese D.O.C.” 30 wines Barbera from 1993 vintage have been compared only regarding their sensory characteristics. An unstructured scale card, composed by 15 descriptors have been used.