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Recovering complete plant root system architectures from soil via X-ray μ-Computed Tomography
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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3615952/ https://www.ncbi.nlm.nih.gov/pubmed/23514198 http://dx.doi.org/10.1186/1746-4811-9-8 |
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author | Mairhofer, Stefan Zappala, Susan Tracy, Saoirse Sturrock, Craig Bennett, Malcolm John Mooney, Sacha Jon Pridmore, Tony Paul |
author_facet | Mairhofer, Stefan Zappala, Susan Tracy, Saoirse Sturrock, Craig Bennett, Malcolm John Mooney, Sacha Jon Pridmore, Tony Paul |
author_sort | Mairhofer, Stefan |
collection | PubMed |
description | 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 backward-looking 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. |
format | Online Article Text |
id | pubmed-3615952 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-36159522013-04-04 Recovering complete plant root system architectures from soil via X-ray μ-Computed Tomography Mairhofer, Stefan Zappala, Susan Tracy, Saoirse Sturrock, Craig Bennett, Malcolm John Mooney, Sacha Jon Pridmore, Tony Paul Plant Methods Software 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 backward-looking 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. BioMed Central 2013-03-20 /pmc/articles/PMC3615952/ /pubmed/23514198 http://dx.doi.org/10.1186/1746-4811-9-8 Text en Copyright © 2013 Mairhofer et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Mairhofer, Stefan Zappala, Susan Tracy, Saoirse Sturrock, Craig Bennett, Malcolm John Mooney, Sacha Jon Pridmore, Tony Paul Recovering complete plant root system architectures from soil via X-ray μ-Computed Tomography |
title | Recovering complete plant root system architectures from soil via X-ray μ-Computed Tomography |
title_full | Recovering complete plant root system architectures from soil via X-ray μ-Computed Tomography |
title_fullStr | Recovering complete plant root system architectures from soil via X-ray μ-Computed Tomography |
title_full_unstemmed | Recovering complete plant root system architectures from soil via X-ray μ-Computed Tomography |
title_short | Recovering complete plant root system architectures from soil via X-ray μ-Computed Tomography |
title_sort | recovering complete plant root system architectures from soil via x-ray μ-computed tomography |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3615952/ https://www.ncbi.nlm.nih.gov/pubmed/23514198 http://dx.doi.org/10.1186/1746-4811-9-8 |
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