A Model-Based Approach to High Performance Phenotyping

Abstract

Breeding pest resistant crops can reduce the application of plant protection products. This in turn will significantly reduce biotical stress of the plants, and damage to the environment. To enable greater efficiency in crop breeding and to optimize decision making in crop management, there is an increasing demand for non-biased and faster assessment of plant traits in lab and field. Within a subproject of CROP.SENSe.net, an interdisciplinary research network of Bonn University and the research centre Jülich, we are working on a non-destructive solution to analyze and screen plant phenotypes. We aim for complete and precise 3D reconstructions of plants based on sensor data. To meet the challenge of occlusions and self-occlusions in sensor-based measurements, we employ a model-based approach "to make hidden object parts visible." First results show that important breeding characteristics can be derived by combining the visible exterior plant components with the model-induced interior plant components.