Future projections for chilling and heat forcing for European vineyards

Climate change is increasing the frequency and severity of environmental hazards (e.g., prolonged drought), and even non-extreme climate events (e.g., a period of slightly warmer temperatures) can lead to extreme impacts when they occur simultaneously with other (non-extreme) events.

The project REALISM (regionality and circular economy in food products to counteract the Metabolic Syndrome (M.S.)) was initiated to develop antioxidant-rich food products with the ability to reduce the risk of developing the M.S.

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.

Vineyard nutrient management is crucial for reaching production-specific quality standards, yet timely evaluation of nutrient status remains challenging. The existing sampling protocol of collecting vine tissue (leaves and/or petioles) at bloom or veraison is time-consuming. Additionally, this sampling practice is too late for in-season fertilizer applications (e.g. N is applied well before bloom). Therefore alternative early-season protocols are necessary to predict the vine nutrient demand for the upcoming season. The main goals of this project are to 1) optimize existing tissue sampling protocols; 2) determine the amount of nutrients removed at the end of the growing season.

Many high quality Open Source scientific applications have been available for a long time. Some of them have proved to be particularly useful for carrying out the usual activities involved in viticultural research projects, such as statistical analyses (including spatial analyses), GIS work, database management (possibly integrated with statistical and spatial analysis) and even “low-level” often highly time-consuming activities (e.g. repetitive task on text files).