Fioriani 800 x 265
Fabio Fiorani, Forschungszentrum Jülich, IBG2 Plant Sciences, Germany
Martin Weih, Plant Production Ecology, SLU
Ekologicentrum, Tammsalen
14:30 - 15:30
Application of plant phenotyping technologies from the lab to the field: state-of the art, trends and challenges

During the last ten years in Europe and worldwide there has been increasing interest and investments in building infrastructure for high-throughput plant phenotyping. Current developments encompass the application of various imaging technologies, non-contact sensors and remote sensing platforms for the retrieval of multi-dimensional datasets targeting structural and functional traits that impact plant productivity both for plants growing in controlled environment and in field trials. In this presentation I will briefly review the state-of-the art of plant phenotyping and introduce in particular the platforms (imaging and volumetric measurements of organs in controlled environment and in the field) that we developed at the Institute of Plant Sciences in Jülich for tackling research questions linked to the quantitative assessment of phenotypic plasticity of shoot and root growth. One major area of our research is dedicated to root development and studies of root architecture with a variety of techniques, ranging from dedicated facilities based on cultivation and 2D automated imaging of rhizoboxes to the use of MRI specifically for reconstruction of root structures in 3D. Field platforms include proximal and remote sensing of canopy structure using 2D and 3D imaging methodologies and probing of photosynthetic capacity by LIFT (Laser Induced Fluorescence Transients) and SIF (Sun Induced Fluorescence). Examples will focus on economically important crop model species. I will conclude the presentation by shortly highlighting major projects that make possible our plant phenotyping infrastructure developments (DPPN, German Plant Phenotyping Network) and access by user groups to European plant phenotyping installations (EPPN2020, European Plant Phenotyping Network).