The impact of leaf canopy management on eco-physiology, wood chemical properties and microbial communities in root, trunk and cordon of Riesling grapevines (Vitis vinifera L.)

Varietal innovation is a major lever for meeting the challenges of the agro-ecological transition of vi-neyards and their adaptation to climate change. To date, selection work has already begun in the Bordeaux region through the Newvine project. The aim of this project is to create new vine varieties with resistance to mildew and powdery mildew, adapted to the climatic conditions of the Bordeaux region and enabling the production of wines that are in line with consumer tastes and the expected typicity of Bordeaux wines.

PPhloem transport of assimilates provides the materials needed for the growth and development of reproductive structures, storage and developing organs, and has long been recognized as a major determinant in crop yield.

Temperature extremes affect grapevine physiology, as well as grape quality and production. In most grape growing regions, frost or heat wave events are rare and as such conducting a risk analysis using robust statistics makes the use of long term daily data necessary.

Il lavoro di zonazione riveste un ruolo importante per capire le potenzialità e la vocazionalità di una specifica area viticola. La viticoltura dovrebbe essere vista in funzione dell’obiettivo enologico che si vuole realizzare e quindi particolare importanza riveste il risultato delle vinificazioni delle uve provenienti dai vigneti delle diverse aree della zona di produzione oggetto d’indagine. La zonazione dell’area a DOC Monti Lessini Durello ha preso in esame la varietà “Durella”, vitigno autoctono del territorio, che rappresenta la maggior parte della produzione vitivinicola della zona.

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.