Terroir 1996 banner
IVES 9 IVES Conference Series 9 Zonificación climática de las D.O. Rueda y Toro y vinos de la tierra de medina del campo

Zonificación climática de las D.O. Rueda y Toro y vinos de la tierra de medina del campo

Abstract

La producción vitícola es el resultado de una serie de factores influyentes (variedad, patron) dentro de un medio ecológico­-climatico-edafico, en el que se interactua por medio de técnicas de cultivo adecuadas.
En la caracterización climática del viñedo estan presentes tanto los elementos tradicionales (temperatura, precipitación, insolación, etc.) así como los factores geográficos (latitud y longitud, altitud, orientación, exposición, proximidad a masas de agua, etc).
Para ver la influencia sobre el vinedo, en las distintas fases de su ciclo vegetativo, se cuantifican y se analizan los parametros mas relevantes en las D.O. Rueda y Toro, Tierra de Vinos.
Las caracteristicas climáticas más destacables de la región pueden ser resumidas (Garcia Femandez, 1986) como sigue:
– clima continental determinado por los efectos de encajamiento y aislamiento definidos por las cadenas montañosas que la rodean.
– rigurosos ( crudos) y largos inviemos: bajas temperaturas medias y generalización de los val ores negativos de las temperaturas medias de las minimas del mes de enero, minimas absolutas acusadamente bajas y largo periodo invernal.
– veranos cortos, relativamente suaves y con fuertes oscilaciones térmicas, con periodos estivales fríos y otros de calor riguroso.
– contrastes acusados en la cuantía y bajos indices de precipitaciones.
– aridez estival sensible y contrastada: acusada aridez estival, complejidad de la precipitación estival, duración de la aridez estival.
– régimen de precipitaciones con contrastes y matices con predominio de la de invierno y primavera.

 

DOI:

Publication date: February 24, 2022

Issue: Terroir 2000 

Type: Article

Authors

Pérez A, Gómez-Miguel V., Sotés V.

Escuela Técnica Superior de Ingenieros Agrónomos

Tags

IVES Conference Series | Terroir 2000

Citation

Related articles…

Podcasts – Terroir Congress 2020

All about “Australian grapevine stories”

Effects of different crop load and pruning aplications on vi̇ne growing, grape yi̇eld and quality parameters of early sweet (Vitis vinifera L.) grape variety

It is important to examine the yield quality elements of table grape varieties. There are great differences in winter and summer pruning of the early sweet grape variety. For this reason, in the study, the effects of different crop loads and pruning processes on grape yield, quality characteristics and vine development in the early sweet (vitis vinifera L.) Grape variety were investigated.

Cumulative effect (6 years) of deficit irrigation in two important cultivars of Douro region, Portugal

Numerous studies have demonstrated the importance of irrigation in improving the grape yield and quality in areas with arid and semiarid climates, particularly in the context of ongoing climate changes. However, the introduction of irrigation in vineyards of the Mediterranean basin is a matter of debate, in particular in those of the Douro Demarcated Region (DDR), due to the limited number of available studies in this region. The present study aimed to evaluate how different irrigation deficits for 6 years would influence production and must quality in Touriga Francesa (TF) and Touriga Nacional (TN) varieties.

Vine environment interaction as a method for land viticultural evaluation. An experience in Friuli Venezia Giulia (N-E of Italy)

For a long time environment was known as one of the most important factors to characterize the quality of wines but at the same time it appears very difficult to distinguish inside the “terroir” the role of the single factor. These remarks partially explain why methods for viticultural evaluation are often quite different (Amerine et al., 1944; Antoniazzi et al., 1986; Asselin et al., 1987; Astruc et al., 1980; Bonfils, 1977; Boselli, 1991; Colugnati, 1990; Costantinescu, 1967; Costantini et al., 1987; Dutt et al., 1981; Falcetti et al., 1992; Fregoni et al., 1992; Hidalgo, 1980; Intrieri et al., 1988; Laville, 1990; Morlat et al., 1991; Scienza et al., 1990; Shubert et al., 1987; Turri et al., 1991).

Effect of multi-level and multi-scale spectral data source on vineyard state assessment

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.