The concept of terroir: what place for microbiota?

The viticulture aiming at the production of high quality wine is very important for the landscape conservation, because it allows to combine high farmer income with soil conservation

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.

Different “landscape unit” have been identified in Bolgheri area (a viticultural appellation in the Tirrenian coast of Tuscany) by the aid of pedological, landscape and agronomic observations in the 1992-1993 period. In all cultivar (Sangiovese, Cabernet Sauvignon and Merlot) x landscape unit combinations, experimental plots were chosen in homogeneous vineyards, single cordon trained (about 3300-4500 vines/hectare). Grape maturation was studied by weekly samples of berries from veraison to vintage in the 1992-1995 period. At harvest yield and must composition traits were measured and, from the most représentative plots, sixty kilograms of grapes were harvested each year and vinified according to a standardised scheme. Wines were evaluated by standard chemical and sensory analyses.

It is well known that high oxygen levels and high ageing temperatures are detrimental to white wine’s composition and ageing capacity. However, these results, though valuable

For characterization, sensory designing and authentication rapid analytical technologies have become available. Some, like Proton Transfer Reaction Mass Spectrometry allow a rapid spectrum of the volatile compounds of wines. Combined with chemometrics wines can be characterized. The same approach can be used to calculate the results of virtual mixtures and allow formulation of constant quality blends. Other new techniques and portable devices based on spectroscopy allow measurements on production sites and in grocery stores, even for the smart consumer. We will present some examples of the application of these techniques for authentication of wines, both in the laboratory and on site.