Recovering complete plant root system architectures from soil via X-ray μ-computed tomography

Mairhofer, Stefan, Zappala, Susan, Tracy, Saoirse, Sturrock, Craig, Bennett, Malcolm J., Mooney, Sacha J. and Pridmore, Tony (2013) Recovering complete plant root system architectures from soil via X-ray μ-computed tomography. Plant Methods, 9 . 8/1-8/7. ISSN 1746-4811

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Background: X-ray micro-Computed Tomography (μCT) offers the ability to visualise the three-dimensional

structure of plant roots growing in their natural environment – soil. Recovery of root architecture descriptions from X-ray CT data is, however, challenging. The X-ray attenuation values of roots and soil overlap, and the attenuation values of root material vary. Any successful root identification method must both explicitly target root material and be able to adapt to local changes in root properties.

RooTrak meets these requirements by combining the level set method with a visual tracking framework and has been shown to be capable of segmenting a variety of plant roots from soil in X-ray μCT images. The approach provides high quality root descriptions, but tracks root systems top to bottom and so omits upward-growing (plagiotropic) branches.

Results: We present an extension to RooTrak which allows it to extract plagiotropic roots. An additional backwardlooking

step revisits the previous image, marking possible upward-growing roots. These are then tracked, leading to efficient and more complete recovery of the root system. Results show clear improvement in root extraction, without which key architectural traits would be underestimated.

Conclusions: The visual tracking framework adopted in RooTrak provides the focus and flexibility needed to

separate roots from soil in X-ray CT imagery and can be extended to detect plagiotropic roots. The extended

software tool produces more complete descriptions of plant root structure and supports more accurate computation of architectural traits.

Keywords: Root systems architecture, 3D, X-ray Computed Tomography, Image analysis, Root phenotyping

Item Type: Article
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Identification Number:
Depositing User: de Sousa, Mrs Shona
Date Deposited: 10 Apr 2014 12:49
Last Modified: 04 May 2020 16:35

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