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Semiautomated 3D Root Segmentation and Evaluation Based on X-Ray CT Imagery.

Stefan GerthJoelle ClaußenAnja EggertNorbert WörleinMichael WainingerThomas WittenbergNorman Uhlmann
Published in: Plant phenomics (Washington, D.C.) (2021)
Using CTX volume data of full-grown bean plants as well as time-resolved (3D + time) growth studies of cassava plants, RootForce produces similar (and much faster) results compared to manual segmentation of the regarded root architectures. Furthermore, RootForce enables the user to obtain traits not possible to be calculated before, such as total root volume (V root), total root length (L root), root volume over depth, root growth angles (θ min, θ mean, and θ max), root surrounding soil density D soil, or form fraction F. Discussion. The proposed RootForce tool can provide a higher efficiency for the semiautomatic high-throughput assessment of the root architectures of different types of plants from large-scale CTX. Furthermore, for all datasets within a growth experiment, only a single set of parameters is needed. Thus, the proposed tool can be used for a wide range of growth experiments in the field of plant phenotyping.
Keyphrases
  • high throughput
  • deep learning
  • computed tomography
  • escherichia coli
  • high resolution
  • multidrug resistant
  • optical coherence tomography
  • big data
  • pet ct