Main subject area: 3D-imaging; Canopy model; DeepLearning; Plant phenotyping
Grain yield of perennial grain crops (e.g. Intermediate wheatgrass) is low – a bottle neck for domestication. Due to their complex genomic structure, phenomic selection that relies on intensive phenotyping on plant traits can potentially be used for development of these novel crops. This requires visualization of grain shape, spike geometry and canopy architecture high-throughput which can speed up the identification of ideal plant candidates with greater grain yield potential. This master project aims to pipeline the process of plant canopy visualization in 3D by acquiring images and constructing models from thousands of individual plants.
Any time
Blichers Alle 20, Tjele, 8830-DK
30 ECTS: Theoretical thesis based on literature studies and/or analysis of issued and edited data sets.
45 or 60 ECTS: Experimental theses in
The master student will mainly learn and work on some of the followings: data acquisition (13C pulse-labelling; plant/soil analysis), data processing, data analysis (R program).
Relevant articles
Peixoto L, Olesen JE, Elsgaard L, et al (2022) Deep-rooted perennial crops differ in capacity to stabilize C inputs in deep soil layers. Scientific Reports 12:. https://doi.org/10.1038/s41598-022-09737-1
