Un “GIS” agronomico per l’area a DOC dei Colli Euganei

Wine quality is defined by sensory and physico-chemical characteristics. In particular, sensory features are very important since they strongly condition wine acceptability by consumers. However, the evaluation of sensory quality can be subjective, unless performed by a tasting panel of experienced tasters. Therefore, it is of great relevance to establish relationships between objective chemical parameters and sensory perceptions, even though the complexity of wine composition makes it difficult. In this sense, more reliable relationships can be found for a particular wine typology or variety. The present study aimed to predict the perceived sensory quality from the physico-chemical parameters of ‘Barbera d’Asti’ DOCG red wines (Italy).

In the context of global warming, water scarcity is becoming an increasing issue worldwide. However, the reference method to characterize vine water deficit is based on water potential measurement, which is a destructive and discontinuous method. The current climatic context emphasizes the need for more precise and more continuous vineyard water use measurements in order to optimize irrigation and vine water deficit monitoring.

En France, la filière A.O.C. cidricole emploie de plus en plus de levures initialement sélectionnées pour les fermentations des vins. Le risque d’une uniformisation organoleptique ou d’un marquage

A set of Syrah plots covering a wide range of terroirs distributed in the vineyards of the Rhone Valley and the Mediterranean South is examined through their oenological and sensory characteristics. The multidimensional analysis of data leads to the following groupings: (1) A group of unstructured wines with a simple aromatic profile dominated by fruity-floral notes; they come from plots where the ripening conditions have been disturbed by unfavorable climatic conditions, or an excess harvest.

Many farming operations aim at controlling the leaf area of the vine according to its load. There are several techniques, direct and indirect, of estimate of this leaf area in a specific way, but impossible to implement at great scales. These last years, research in airborne and satellite remote sensing made it possible to show that a multispectral index of vegetation, computed from measurements of reflectances (red and near infrared), the « Normalised Difference Vegetation Index » (NDVI), is well correlated to the « Leaf Area Index » (leaf area per unit of ground) of the vine. Nevertheless these methods of acquisition and processing data are rather constraining and complex.