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High throughput phenotyping of morpho-anatomical stem properties using X-ray computed tomography in sorghum
BACKGROUND: In bioenergy/forage sorghum, morpho-anatomical stem properties are major components affecting standability and juice yield. However, phenotyping these traits is low-throughput, and has been restricted by the lack of a high-throughput phenotyping platforms that can collect both morphologi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6043981/ https://www.ncbi.nlm.nih.gov/pubmed/30008795 http://dx.doi.org/10.1186/s13007-018-0326-3 |
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author | Gomez, Francisco E. Carvalho, Geraldo Shi, Fuhao Muliana, Anastasia H. Rooney, William L. |
author_facet | Gomez, Francisco E. Carvalho, Geraldo Shi, Fuhao Muliana, Anastasia H. Rooney, William L. |
author_sort | Gomez, Francisco E. |
collection | PubMed |
description | BACKGROUND: In bioenergy/forage sorghum, morpho-anatomical stem properties are major components affecting standability and juice yield. However, phenotyping these traits is low-throughput, and has been restricted by the lack of a high-throughput phenotyping platforms that can collect both morphological and anatomical stem properties. X-ray computed tomography (CT) offers a potential solution, but studies using this technology in plants have evaluated limited numbers of genotypes with limited throughput. Here we suggest that using a medical CT might overcome sample size limitations when higher resolution is not needed. Thus, the aim of this study was to develop a practical high-throughput phenotyping and image data processing pipeline that extracts stem morpho-anatomical traits faster, more efficiently and on a larger number of samples. RESULTS: A medical CT was used to image morpho-anatomical stem properties in sorghum. The platform and image analysis pipeline revealed extensive phenotypic variation for important morpho-anatomical traits in well-characterized sorghum genotypes at suitable repeatability rates. CT estimates were highly predictive of morphological traits and moderately predictive of anatomical traits. The image analysis pipeline also identified genotypes with superior morpho-anatomical traits that were consistent with ground-truth based classification in previous studies. In addition, stem cross section intensity measured by the CT was highly correlated with stem dry-weight density, and can potentially serve as a high-throughput approach to measure stem density in grass stems. CONCLUSIONS: The use of CT on a diverse set of sorghum genotypes with a defined platform and image analysis pipeline was effective at predicting traits such as stem length, diameter, and pithiness ratio at the internode level. High-throughput phenotyping of stem traits using CT appears to be useful and feasible for use in an applied breeding program. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13007-018-0326-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6043981 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-60439812018-07-13 High throughput phenotyping of morpho-anatomical stem properties using X-ray computed tomography in sorghum Gomez, Francisco E. Carvalho, Geraldo Shi, Fuhao Muliana, Anastasia H. Rooney, William L. Plant Methods Methodology BACKGROUND: In bioenergy/forage sorghum, morpho-anatomical stem properties are major components affecting standability and juice yield. However, phenotyping these traits is low-throughput, and has been restricted by the lack of a high-throughput phenotyping platforms that can collect both morphological and anatomical stem properties. X-ray computed tomography (CT) offers a potential solution, but studies using this technology in plants have evaluated limited numbers of genotypes with limited throughput. Here we suggest that using a medical CT might overcome sample size limitations when higher resolution is not needed. Thus, the aim of this study was to develop a practical high-throughput phenotyping and image data processing pipeline that extracts stem morpho-anatomical traits faster, more efficiently and on a larger number of samples. RESULTS: A medical CT was used to image morpho-anatomical stem properties in sorghum. The platform and image analysis pipeline revealed extensive phenotypic variation for important morpho-anatomical traits in well-characterized sorghum genotypes at suitable repeatability rates. CT estimates were highly predictive of morphological traits and moderately predictive of anatomical traits. The image analysis pipeline also identified genotypes with superior morpho-anatomical traits that were consistent with ground-truth based classification in previous studies. In addition, stem cross section intensity measured by the CT was highly correlated with stem dry-weight density, and can potentially serve as a high-throughput approach to measure stem density in grass stems. CONCLUSIONS: The use of CT on a diverse set of sorghum genotypes with a defined platform and image analysis pipeline was effective at predicting traits such as stem length, diameter, and pithiness ratio at the internode level. High-throughput phenotyping of stem traits using CT appears to be useful and feasible for use in an applied breeding program. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13007-018-0326-3) contains supplementary material, which is available to authorized users. BioMed Central 2018-07-13 /pmc/articles/PMC6043981/ /pubmed/30008795 http://dx.doi.org/10.1186/s13007-018-0326-3 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology Gomez, Francisco E. Carvalho, Geraldo Shi, Fuhao Muliana, Anastasia H. Rooney, William L. High throughput phenotyping of morpho-anatomical stem properties using X-ray computed tomography in sorghum |
title | High throughput phenotyping of morpho-anatomical stem properties using X-ray computed tomography in sorghum |
title_full | High throughput phenotyping of morpho-anatomical stem properties using X-ray computed tomography in sorghum |
title_fullStr | High throughput phenotyping of morpho-anatomical stem properties using X-ray computed tomography in sorghum |
title_full_unstemmed | High throughput phenotyping of morpho-anatomical stem properties using X-ray computed tomography in sorghum |
title_short | High throughput phenotyping of morpho-anatomical stem properties using X-ray computed tomography in sorghum |
title_sort | high throughput phenotyping of morpho-anatomical stem properties using x-ray computed tomography in sorghum |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6043981/ https://www.ncbi.nlm.nih.gov/pubmed/30008795 http://dx.doi.org/10.1186/s13007-018-0326-3 |
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