Terroir influence on growth, grapes and grenache wines in the AOC priorat, northeast Spain

Context and purpose of the study. The primary fungal diseases affecting grapevines in Europe are downy mildew and powdery mildew.

It is often said that wine is a complex matrix and the chemical analysis of wine with the thousands of compounds detected and often measured is proof. New technologies can assist not only in separating and identifying wine compounds, but also in providing information about the sample as a whole. Information-rich techniques can offer a fingerprint of a sample (untargeted analysis), a comprehensive view of its chemical composition. Applying statistical analysis directly to the raw data can significantly reduce the number of compounds to be identified to the ones relevant to a particular scientific question. More data can equal more information, but also more noise for the subsequent statistical handling.

AIM: Pinot Noir (PN) wines produced in South Tyrol were profiled with the aim to provide guidelines for the oenologist to reach specific winemaking goals in terms of typicity and quality.

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.

Geospatial technologies have significant contribution to viticulture, especially in small-scale vineyards, which require precise management. Geospatial data collected by modern technologies, such as Unmanned Aerial Vehicle (UAV) and satellite imagery, can be processed by modern software and easily be stored and transferred to GIS environments, highlighting important information about the health of vine plants, the yield of grapes and the wine, especially in wine-making varieties. The identification of field variability is very important, particularly for the production of high quality wine. Modern geospatial data management technologies are used to achieve an easy and effortless localization of the fields’ variability.