Multidisciplinary strategies for understanding ill-defined concepts

Face à la concurrence mondiale, il est indispensable de s’orienter vers des vins de qualité, marqués par une typicité et une authenticité inimitables. Le terroir représente, pour une région donnée, un patrimoine unique et non reproductible, qui peut être valorisé à travers l’origine et les caractéristiques sensorielles du vin.

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.

Ovalbumin (ova), a natural clarifying protein, is particularly suitable for clarifying red wines. It helps improve the tannic and polyphenolic stability of the wine by removing the most astringent tannins and contributing to soften and refine the structure. Ova binds to suspended particles, proteins, polysaccharides, and, to a lesser extent, tannins through electrostatic and hydrophobic interactions, forming large complexes that can be removed from the wine through fining and/or filtration before bottling.

Agriculture is one of the largest contributors to environmental pollution and causing significant impacts on human health, ecosystems, and resource availability.

The own-rooted vineyard of Santorini is a unique case of vineyard worldwide that is been cultivated for thousands of years. On the island’s volcanic soil, the vines are still cultivated with traditional techniques, which are adapted to the specific and extreme weather conditions that prevail on it. While climate change is a reality in the Mediterranean region, will Santorini vineyard endure its impact? The study of the traditional training systems, techniques and vine density, as well as the application of sustainable solutions (cover crops and use of kaolin etc.) revealed sustainable methods for the adaptation of the local viticulture to new climatic phenomena that tend to be more and more frequent in the region due to climate change.