Physiological Breeding

We develop high-throughput field phenotyping methodologies to enhance the genetic gain of yield and yield stability of wheat and other crops in the field. Specifically, we aim i) to achieve a deeper understanding of the genetic control of developmental processes during critical phases of crop development and ii) to develop phenotyping methodologies and genetic crop models to predict the performance of new breeding lines depending on the target environment and climate scenario. To achieve this, we follow two lines of research: i) continuous phenotyping of wheat throughout its development using the Field Phenotyping Platform (FIP) and the Phenofly infrastructure and ii) intense and close collaboration with breeders in the framework of TraitSpotting to close the gap between crop physiology and applied breeding. The data are managed by means of the crop phenotyping database (CroPyDB).
Achievements: We developed a range of high-throughput methodologies to evaluate the performance of wheat as it develops during the growing season (external pageHund et al. 2019call_made). These traits comprise i) temperature-response and phenological development during winter (Grieder, Hund, and Walter 2015; Yu et al. 2017) and during stem elongation (Kronenberg et al. 2017; 2020) ii) the rate and timing of senescence (Anderegg et al. 2020) as well as the quantification of Septoria Tritici Blotch (Anderegg et al. 2019; Yu et al. 2018). To upscale these methodologies to breeding application, the group recently put more focus on drone-based phenotyping of large numbers of field plots (ethz.ch/traitspotting) including flight planning (Roth et al., 2018) and protocols for thermal imaging (Perich et al., 2020). The group also developed a method for repeated multi-view imaging for estimating seedling tiller counts of wheat genotypes using drones (Roth et al., 2020)