Research Projects - Selection

This project aims to study the combined effects of the two stressors (heat and drought stress) on the grapevine physiology response and its consequences on berry metabolism and composition with particular focus on key metabolites determining wine quality such as flavonoids and aroma compounds.

The project investigates the response of iron deficiency and high bicarbonate contents in soils of grapevine rootstocks. The novelty of our approach is the application of standardized experimetns with high end analyses on different levels and the focus on processes yet unknown in grapevine rootstocks.

The PlasticGrape project will study the grapevine metabolic plasticity under drought by characterizing the vine metabolism response to water stress in two climatically distinct environments (Tulln-Austria and Vipava-Slovenia).

In 2018 and 2019 pot experiments were conducted with vines in order to test different substrates and nutrition amendments to prevent chlorose symptoms under lime stress conditions. The fertilizer BioAgenasol strongly promoted plant growth and root developments enabling the plant to cope with high lime stress situations much better as comparable fertilizers. A direct translation of results from pot experiments to vineyards is not possible as vines are prennial plants. The presented project is a 2-year experiment in vineyards to determine effects of different fertilizers including BioAgenasol on vegetative and generative parameters of vines including fruit parameters. 

The project aims to promote and aggregate Innovative Solutions focussed on the participative development of fruit varieties and on a fruit plant production system dedicated to the organic farming system.

The frost protection measures presently applied in wine and fruit growing are examined in this project for their actual effect. They are improved and new measures are developed. In addition to that a digital tool is developed in the course of the project, which links data and information in an intelligent way and delivers forecasts as well as recommendations for actions for farms.

Transition from high input-dependent green-revolution towards a future resource efficient agronomy requires technologies facilitating informed management decisions that optimally relay on in vivo plant diagnostics. The aim of this project is to develop a physiological plant trait digitalization pipeline that harmonizes throughput of spectral imaging and physiological reference data acquisition with dataset structure requirements for the development of feature detection and prediction models. Application of the novel approach is demonstrated for grapevine stress detection in response to water deficit which is relevant for sustainable irrigation strategies.