Rhizosphere traits enhancing yield resilience to drought in modern cropping systems
Contact: Prof. Dr. Johanna Pausch, University of Bayreuth
Project team: University of Bayreuth, University of Copenhagen, Technische Universität München, Bavarian State Research Center for Agriculture (LfL), Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research (IMK-IFU)
Duration: 01/02/2020 - 31/01/2024
Link Website: http://www.bayceer.uni-bayreuth.de/rhizotraits/
Our aim is to gain a systematic understanding of how rhizosphere traits impact soil-plant interactions and contribute to increasing the quantity and quality of crop yields under varying climatic conditions. Our findings will be translated into recommendations for agricultural practices and plant breeding in order to increase the resilience to drought in modern cropping systems.
Over the past 50 years, breeding programs primarily focused on increasing yield. Crops were selected under optimal water and nutrient supply with little attention having been drawn to plant’s ability to adapt to erratic weather conditions such as drought. This has likely led to a loss of genes that are critical for the plasticity and functionality of the rhizosphere and that are associated with efficient resource acquisition. We propose that old varieties and landraces have a higher capacity to buffer the strong variability in yield by expressing a higher plasticity of rhizosphere traits under extreme climatic conditions.
RhizoTraits pursues a systematic and comprehensive approach based on three aspects:
- laboratory and field experiments with maize and wheat will investigate the influence of key rhizosphere traits on carbon allocation, water and nutrient use efficiency, rhizosphere microbiome selection, soil structure formation, plant biomass production and yield performance
- historical records will be used to identify old plant varieties with a particularly high resistance to drought stress
- the data obtained will be used to further develop a biogeochemical model that allows to predict improved rhizosphere functionality on yields under current and future climatic scenarios.