Interacción mesoclima-suelo en la calidad del vino de Cabernet-Sauvignon en las denominaciones de origen Priorato y Tarragona

Le mot “terroir” dérive du latin “terra”, mais déjà les Romains l’indiquaient comme “locus” ou”loci”, c’est-à-dire un lieu ayant le “genius”destiné à la production d’un produit d’excellente qualité.

Les aires d’appellations de la Côte d’Or résultent d’une sélection humaine empirique, historique et évolutive en adéquation avec les facteurs naturels. Afin de comprendre quels facteurs naturels et humains agissent sur le caractère et l’évolution des terroirs des Côtes de Nuits et de Beaune, une méthodologie de recherche a été développée. Elle s’articule autour de deux axes, la caractérisation physique des lieux-dits viticoles et l’historicité de la qualité de ces lieux-dits. Le travail avec un S.I.G permet d’étudier l’évolution spatiale et temporelle de la qualité.

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.

In the pursuit of increasing sustainability, climate change resiliency and independence of synthetic pesticides in agriculture, the interest of consumers and producers in organic and biodynamic farming is steadily increasing. This is in particular the case for the vitivinicultural industry in Europe, where more and more producers are converting from organic to biodynamic farming. However, clear scientific evidence showing that biodynamic farming improves vine physiology, vine stress resilience, berry or wine quality, or is more sustainable for the environment is still lacking although this issue has been addressed by several research teams worldwide.

The objective of the present work is to evaluate the impact of three S. cerevisiae strains on the comprehensive aroma profile of Albariño wine along its shelf life.