Great highlands wine growing terroir: conditions and expressions

The traditional methods of grape extraction of enochemical compounds use very often mechanical energy by pistons such as the pigeage or mechanical energy produced by must (delestage, pumping over). Recent trend by winemaker is trying to introduce in the fermentation tank, whole berry grape to avoid even minimal oxidation. Unfortunately, the use of the traditional mechanical techniques aforementioned, very often do not guarantee the optimal extraction with residual sugars in the marc. Use of resonance waves (airmixingtm) and a slight overpressure by CO2 (adcftm) permit to work on whole berry guaranteeing the perfect extraction.

Identification and characterisation of terroirs depends on knowledge of environmental parameters, functioning of the grapevine and characteristics of the final product. A network of plots of Sauvignon blanc was delimited in commercial vineyards in proximity to weather stations at 20 localities and their viticultural and oenological response was monitored for a period of seven years. These experimental plots were further characterised with respect to climate, soil and topography.

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.

According to winemakers, wine experts and sommeliers, aromas of wet stone, mineral, struck match and flint in white wines styles, such as those produced from Vitis vinifera L. cv. Chardonnay, are considered to be hallmarks of positive reduction.1,2 In recent years, the production of Chardonnay styles defined by aroma characteristics related to positive reduction has become more desirable among wine experts and consumers. The chemical basis of positive reduction is thought to originate from the concentration of specific volatile sulfur compounds (VSCs), including methanethiol (MeSH) imparting mineral and chalk notes,3 and benzenemethanethiol (BMT) responsible for struck match and flint.1,4

Today, the concept of precision vine management (or site-specific viticulture) has a great relevance. It is based on the practice of a different management in relation to the different features of the crop site. In this way, all practices should be adapted to the land spatial variability and should be linked to the real needs of vines.