Pattern Recognition and
Image Processing Group
Institute of Visual Computing and Human-Centered Technology
Water's Gateway to Heaven
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Quick FactsWater's Gateway to Heaven: 3D imaging and modeling of transient stomatal responses in plant leaves under dynamic environments.
WWTF project LS19-013, Life Sciences 2019, Multimodal Imaging
Duration: Feb/2020 – Jan/2024
|BOKU Wien:||Guillaume Théroux-Rancourt, Daniel Tholen|
|Universität Wien:||Ingeborg Lang|
|TU Wien:||Walter G. Kropatsch, Jiří Hladůvka|
DescriptionStomata are tiny pores on the surface of plant leaves. Although they only cover a small part of the leaf surface, they control the exchange of gases with the atmosphere and thus play a central role in the global water and carbon cycle.
Opening and closing of the stomata must be regulated so that CO2 can get into the plant for photosynthesis, but at the same time excessive water loss is avoided. Stomata have to react to the environment, and the speed of this reaction affects the exchange of CO2 and water with the atmosphere and thus the efficiency of water consumption.
In this innovative project by BOKU, Vienna University of Technology and Vienna University, we will observe the three-dimensional shape changes of cells in living leaves by combining high-resolution X-ray micro-tomography (μCT) and fluorescence microscopy. In order to take full advantage of the large data volume, new computer methods are being developed that automatically segment these images and track the change in the individual cells over time. This is intended to answer longstanding questions about stoma movements. A better understanding of the anatomical basis and the mechanical process of stoma movement will provide new approaches to regulating stomata and thus help to optimize the productivity and water consumption of plants.
The contribution of Vienna University of Technology focuses on the processing and analysis of the dynamic image data in three dimensions. In order to be able to make full use of the large data volume, new equivariant neural networks are first developed that automatically segment these images. In order to track the change of the individual cells over time, hierarchies of abstract topological cell complexes are used, which will reduce the image data to a neighboring structure of the plant cells without losing the relation to the original data. This makes it possible to verify hypotheses at any time that arise during the course of the biological analysis but may not have been known at the time the hierarchy was built. Furthermore, this structure of the plant cells is to be used to simulate dynamic processes.