Les sols du cru de Bonnezeaux, Thouarcé, Anjou, France

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.

Grapevine (Vitis vinifera L.) exhibits a high level of genetic and phenotypic diversity among the approximately 6000 cultivars recorded. This perennial crop is highly vulnerable to numerous fungal diseases, including esca, which is a complex vascular pathology that poses a significant threat to the wine sector, as there is currently no cost-efficient curative method[1]. In this context, an effective approach to mitigate the impact of such diseases is by leveraging the crop’s genetic diversity. Indeed, susceptibility to esca disease appears to vary between cultivars, under artificial or natural infection. However, the mechanisms and varietal characteristics underlying cultivar susceptibility to esca are still unknown.

Cover crops are acknowledged to be an interesting tool to produce
higher quality grapes in red varieties, as they generally reduce vine vigour and yield. However, their incidence in white wine quality is not clear, since higher nitrogen availability can play an important positive
role, and cover crops may compete for this nutrient. The possible reduction in available nitrogen can also modify the fermentation processes, as well as the synthesis of aromas in the wine. The aim of this work was to evaluate the long-term effect of a grass cover crop on grape and wine quality.

In the context of LIFE project MIDMACC (LIFE18 CCA/ES/001099), several pilots have been installed in vineyards in mid mountain areas of Catalonia (NE Spain) to test well stablished agronomic practices to increase the adaptation of Mediterranean mid mountain to climate change. Soil water content (SWC) at three different depths (15, 30 and 45cm) was measured in continuum from August 2020. One pilot (WC) included a well-established green cover (GC), a new GC (NC) and a conventional soil management (CM, tilling+herbicides). NC presented an intermediate state between WC and CM, responding similarly to CM in autumn but quickly reaching similar SWC to WC, then following the same evolution till next spring, with CM presenting lower values along autumn and winter. Then vegetation activation decreased SWC in all plots, (much slower in CM, lacking GC). Sensibility to spring rains is again intermediate for NC, which joins SWC evolution of CM by the end of spring till next autumn. It is expected that NC will resemble WC more and more as its GC develops. In the pilot combining vine training (VSP vs Gobelet) and hillside management (slope vs terrace), no clear pattern could be related with these conditions. However, both terraces seem to be more sensitive to spring rains. A third pilot included new vineyards (7 and 1 year old). In the new vineyard (N), higher canopy development, a spontaneous green cover and row straw resulted in a slower SWC dynamic, not so sensitive to rains but conserving more soil water in spring and most of summer, even with presumably a higher water extraction by vines. In the newest vineyard (VN) the deepest sensor is still sensitive to rain events all over the year and SWC is always highest at this depth, revealing small water capture by vines.

The wine industry is increasingly focused on carbon accounting due to consumer’s demand and the industry’s goal of reducing carbon emissions.