Elementi in traccia e ultratraccia nell’uva: possibili applicazioni ai fini della tracciabilità geografica

Nowadays the use of non-Saccharomyces as starters of alcoholic fermentation (AF) has increased because of the modulation of the organoleptic profile of wines

The challenges of the century for viticulture relate to coping with climate change and the loss of biodiversity in a downturning socio-economic context. Now more than ever, the vine and wine industry needs to be resilient to maintain and ensure a future for its heritage. An innovation of capital importance, in line with recently published research, deals with developing new methods of training our inherited and newly planted vineyards to better withstand environmental variations such as drought and heatwaves but also unevenly distributed rains and temperatures.

The aim of this study is to provide an overview of the terroir of Saint-Romain, Burgundy, based on three main information sources: official data relating to vines (CVI), soil cartography and a survey of winegrowers’ practices.

L’A.O.C. Coteaux du Languedoc est située dans le Sud de la France, dans la partie Ouest de la bordure méditerranéenne. Elle forme un vaste amphithéâtre largement ouvert sur la mer méditerranée. L’Appellation a été constituée en 1960 par le regroupement de 14 anciennes petites appellations d’origine représentant 55 communes éparpillées dans les départements de l’Aude, de l’Hérault et du Gard. Par la suite, plusieurs extensions successives ont conduit à un ensemble actuellement composé de 168 communes.

the phenological evolution is a crucial aspect of grapevine growth and development. Accurate detection of phenological stages can improve vineyard management, leading to better crop yield and quality traits. However, traditional methods of phenological tracking such as on-site observations are time-consuming and labour-intensive. This work proposes a scalable data-driven method to automatically detect key phenological stages of grapevines using satellite data. Our approach applies to vast areas because it solely relies on open and satellite data having global coverage without requiring any in-field data from weather stations or other sensors making the approach extensible to other areas.