Coping with extreme climatic events: some lessons from recent work on grapevine under heat peak

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 spp.) is a globally significant fruit crop and enhancing its agronomic and oenological traits is crucial to meet changing agricultural conditions and consumer demands.

Grapevine is grown grafted in most of the world largely because of Phylloxera. Rootstocks not only provide tolerance to Phylloxera, but also ensure the supply of water and mineral nutrients to the scion. Rootstocks are an important means of adaptation to environmental conditions if we want to conserve the typical features of the currently used scion genotypes. To aid this adaptation, we can exploit the large diversity of rootstocks used worldwide. To fully explore this existing rootstock diversity, this work benefits from the unique GreffAdapt vineyard, in which four scion genotypes were studied onto 55 commercial rootstocks in three blocks. The aim of this study was to characterise rootstock regulation of scion mineral status and how it relates to scion development.

The main challenge faced by viticulture is to improve the quality of the wines, adapting them to the new consumer demands that demand wines with lower alcohol content and greater freshness. In the last 30 years, a clear modification has been observed in the composition of the grape due to climate change

The past three decades of terrestrial remote sensing research have delivered unprecedented insights into our fundamental ability to detect, quantify, and differentiate plant disease (Gold 2021). However, much of our fundamental knowledge in this domain has come from studies in non-agricultural systems and until recently, most agricultural studies, when extant, have focused on tree crops where canopy closure and large plot and plant size facilitate stress detection at low spatial resolution. Recent engineering innovations and advancements in constellation architecture design have refined the accuracy and scalability of airborne and spaceborne sensing platforms, enabling us to monitor diverse specialty crops, including grapevine, planted in smaller, spatially varied fields.