Oospore germination dynamics and disease forecasting model for a precision management of downy mildew 

Weather uncertainty is forcing Mediterranean winegrowers to adopt new irrigation strategies to cope with water scarcity while ensuring a sustainable yield and improved berry and wine quality standards. Therefore, more accurate and high-resolution monitoring of soil water content and vine water status is a major concern. Leaf water potential measured at pre-dawn (PD) is considered to be in equilibrium with soil water potential and is highly correlated with soil water content at the soil depth where roots extract water.

Polyphenols are present in a wide variety of plants and foods such as tea, cacao and grape1. An important sub-class of these compounds is the flavanols present in grapes and wines as monomers (e.g (+)-catechin or (-)-epicatechin), or polymers also called condensed tannins or proanthocyanidins. They have important antioxidant properties2 but their biosynthesis remains partly unknown. Some recent studies have focused on the role of glycosylated intermediates that are involved in the transport of the monomers and may serve as precursors in the polymerization mechanism3, 4. The global objective of this work is to identify flavanol glycosides in grapes or wines, describe their structure and determine their abundance during grape development and in wine.

Two transmittance-based chlorophyll meters (SPAD-502 and CCM-200) were evaluated in estimating chlorophyll (Chl) and nitrogen (N) levels in grapevine leaves.

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.

This work aimed at setting up a multivariate and geostatistical methodology to map natural terroir units of the viticultural areas at the province scale (1:125,000).