«Observatoire Mourvèdre»: (2) climatic mapping for successful plantation of Cv. Mourvèdre

Il Turismo negli anni 2000 si appresta ad essere la più vasta ed estesa impresa presente nel mondo. Se a cio si aggiunge il fatto che il tempo libero risulta essere, per la maggior parte delle persone, la principale aspirazione da considerare ben oltre il proprio benessere eco­nomico, ci si rende conto del perché di una crescente domanda di ecoturismo. Un viaggiare sempre più accorto aile valenze ambientali e tipiche di un territorio.

This study aims at exploiting an undervalued winemaking by-product, wine yeast lees, by developing efficient and food-grade methods for the extraction of yeast glycoproteins. These extracts were then supplemented to wine and their impact on wine properties assessed.

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.

AIM: Quinoa (Chenopodium quinoa) is a non-allergenic pseudocereal with a high protein content

The wine industry faces the consumer’s increasing demand for a sustainable and environmentally-friendly production [1]. This demand has been shared and boosted by the European Union within the European Green Deal in the Farm to Fork strategy that aims to reduce a 50% the pesticide utilisation in farming systems. Among the agronomical approaches so far proposed, the use of mould resitant hybrid varieties -based on crossings of Vitis vinifera with other Vitis spp [2]- with a high tolerance to the attack of vine patogens is gaining the vinegrowers attention and the production area is continuously increasing