Les activités peroxidasiques du raisin de quelques cépages de Roumanie

The effect of cover crop on the water relations, yield and grape composition of Pinot noir vines was investigated during two seasons (2003 and 2004) in a gravely soil located in Tarragona (Spain). Seventeen-year-old vines, grafted onto R110 and trained onto a Ballerina training system, were used.

The Ibero-American Network of Viticulture, a component of the program of agricultural technology of the CYTED (Ibero-American Program of Science and Technology for Development), is developing the project “Zoning Methodology and Application in Viticultural Regions of Ibero-America”.

Yeasts serve as highly versatile tools in oenology. They do more than just perform alcoholic fermentation. Nowadays, yeasts from various species, naturally present in grapes, are selected for specific non-fermentative applications. For example, the use of selected non-saccharomyces at the early stage of winemaking has become a common practice to limit the growth of unwanted microorganisms. When inactivated, yeasts can be fractionated into soluble and insoluble fractions providing a wide range of benefits related to structural components or specific metabolites.

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.

A 3-year study was carried out in order to evaluate the ecophysiology, yield and quality characteristics of Vitis vinifera L. cv. Kékfrankos (syn. Limberger) at Eger-Nagyeged hill (steep slope) and at Eger-Kőlyuktető (flat) vineyard sites located in the Eger wine region, Hungary.