Evidence map›Paper›PMID 39187896›Full record

ArticlePlant methods2024

TopoRoot+: computing whorl and soil line traits of field-excavated maize roots from CT imaging.

Yiwen Ju, Alexander E Liu, Kenan Oestreich, Tina Wang, Christopher N Topp, Tao Ju

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Article in Plant methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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3 citing papers in PubMed.

  1. Article
  2. Improving plant breeding through AI-supported data integration.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Yiwen JuWashington University in Saint Louis, St. Louis, USA.
Alexander E LiuWashington University in Saint Louis, St. Louis, USA.
Kenan OestreichDonald Danforth Plant Science Center, Creve Coeur, USA.
Tina WangMarquette High School, Chesterfield, MO, USA.
Christopher N ToppDonald Danforth Plant Science Center, Creve Coeur, USA.
Tao JuWashington University in Saint Louis, St. Louis, USA. taoju@wustl.edu.

Funding

National Science Foundation NSF DBI-1759836, DBI-1759796, EF-1921728
6 · The paper itself

Abstract

backgroundThe use of 3D imaging techniques, such as X-ray CT, in root phenotyping has become more widespread in recent years. However, due to the complexity of the root structure, analyzing the resulting 3D volumes to obtain detailed architectural root traits remains a challenging computational problem. When it comes to image-based phenotyping of excavated maize root crowns, two types of root features that are notably missing from existing methods are the whorls and soil line. Whorls refer to the distinct areas located at the base of each stem node from which roots sprout in a circular pattern (Liu S, Barrow CS, Hanlon M, Lynch JP, Bucksch A. Dirt/3D: 3D root phenotyping for field-grown maize (zea mays). Plant Physiol. 2021;187(2):739-57. https://doi.org/10.1093/plphys/kiab311 .). The soil line is where the root stem meets the ground. Knowledge of these features would give biologists deeper insights into the root system architecture (RSA) and the below- and above-ground root properties.

resultsWe developed TopoRoot+, a computational pipeline that produces architectural traits from 3D X-ray CT volumes of excavated maize root crowns. Building upon the TopoRoot software (Zeng D, Li M, Jiang N, Ju Y, Schreiber H, Chambers E, et al. Toporoot: A method for computing hierarchy and fine-grained traits of maize roots from 3D imaging. Plant Methods. 2021;17(1). https://doi.org/10.1186/s13007-021-00829-z .) for computing fine-grained root traits, TopoRoot + adds the capability to detect whorls, identify nodal roots at each whorl, and compute the soil line location. The new algorithms in TopoRoot + offer an additional set of fine-grained traits beyond those provided by TopoRoot. The addition includes internode distances, root traits at every hierarchy level associated with a whorl, and root traits specific to above or below the ground. TopoRoot + is validated on a diverse collection of field-grown maize root crowns consisting of nine genotypes and spanning across three years. TopoRoot + runs in minutes for a typical volume size of [Formula: see text] on a desktop workstation. Our software and test dataset are freely distributed on Github.

conclusionsTopoRoot + advances the state-of-the-art in image-based phenotyping of excavated maize root crowns by offering more detailed architectural traits related to whorls and soil lines. The efficiency of TopoRoot + makes it well-suited for high-throughput image-based root phenotyping.

Indexed as

3D imagingComputer graphicsMaize phenotypingRoot system architecture

Identifiers

PMID39187896
PMCPMC11348750

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