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4DRoot: Root phenotyping software for temporal 3D scans by X-ray computed tomography
Currently, plant phenomics is considered the key to reducing the genotype-to-phenotype knowledge gap in plant breeding. In this context, breakthrough imaging technologies have demonstrated high accuracy and reliability. The X-ray computed tomography (CT) technology can noninvasively scan roots in 3D...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9539560/ https://www.ncbi.nlm.nih.gov/pubmed/36212319 http://dx.doi.org/10.3389/fpls.2022.986856 |
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author | Herrero-Huerta, Monica Raumonen, Pasi Gonzalez-Aguilera, Diego |
author_facet | Herrero-Huerta, Monica Raumonen, Pasi Gonzalez-Aguilera, Diego |
author_sort | Herrero-Huerta, Monica |
collection | PubMed |
description | Currently, plant phenomics is considered the key to reducing the genotype-to-phenotype knowledge gap in plant breeding. In this context, breakthrough imaging technologies have demonstrated high accuracy and reliability. The X-ray computed tomography (CT) technology can noninvasively scan roots in 3D; however, it is urgently required to implement high-throughput phenotyping procedures and analyses to increase the amount of data to measure more complex root phenotypic traits. We have developed a spatial-temporal root architectural modeling software tool based on 4D data from temporal X-ray CT scans. Through a cylinder fitting, we automatically extract significant root architectural traits, distribution, and hierarchy. The open-source software tool is named 4DRoot and implemented in MATLAB. The source code is freely available at https://github.com/TIDOP-USAL/4DRoot. In this research, 3D root scans from the black walnut tree were analyzed, a punctual scan for the spatial study and a weekly time-slot series for the temporal one. 4DRoot provides breeders and root biologists an objective and useful tool to quantify carbon sequestration throw trait extraction. In addition, 4DRoot could help plant breeders to improve plants to meet the food, fuel, and fiber demands in the future, in order to increase crop yield while reducing farming inputs. |
format | Online Article Text |
id | pubmed-9539560 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95395602022-10-08 4DRoot: Root phenotyping software for temporal 3D scans by X-ray computed tomography Herrero-Huerta, Monica Raumonen, Pasi Gonzalez-Aguilera, Diego Front Plant Sci Plant Science Currently, plant phenomics is considered the key to reducing the genotype-to-phenotype knowledge gap in plant breeding. In this context, breakthrough imaging technologies have demonstrated high accuracy and reliability. The X-ray computed tomography (CT) technology can noninvasively scan roots in 3D; however, it is urgently required to implement high-throughput phenotyping procedures and analyses to increase the amount of data to measure more complex root phenotypic traits. We have developed a spatial-temporal root architectural modeling software tool based on 4D data from temporal X-ray CT scans. Through a cylinder fitting, we automatically extract significant root architectural traits, distribution, and hierarchy. The open-source software tool is named 4DRoot and implemented in MATLAB. The source code is freely available at https://github.com/TIDOP-USAL/4DRoot. In this research, 3D root scans from the black walnut tree were analyzed, a punctual scan for the spatial study and a weekly time-slot series for the temporal one. 4DRoot provides breeders and root biologists an objective and useful tool to quantify carbon sequestration throw trait extraction. In addition, 4DRoot could help plant breeders to improve plants to meet the food, fuel, and fiber demands in the future, in order to increase crop yield while reducing farming inputs. Frontiers Media S.A. 2022-09-23 /pmc/articles/PMC9539560/ /pubmed/36212319 http://dx.doi.org/10.3389/fpls.2022.986856 Text en Copyright © 2022 Herrero-Huerta, Raumonen and Gonzalez-Aguilera. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Herrero-Huerta, Monica Raumonen, Pasi Gonzalez-Aguilera, Diego 4DRoot: Root phenotyping software for temporal 3D scans by X-ray computed tomography |
title | 4DRoot: Root phenotyping software for temporal 3D scans by X-ray computed tomography |
title_full | 4DRoot: Root phenotyping software for temporal 3D scans by X-ray computed tomography |
title_fullStr | 4DRoot: Root phenotyping software for temporal 3D scans by X-ray computed tomography |
title_full_unstemmed | 4DRoot: Root phenotyping software for temporal 3D scans by X-ray computed tomography |
title_short | 4DRoot: Root phenotyping software for temporal 3D scans by X-ray computed tomography |
title_sort | 4droot: root phenotyping software for temporal 3d scans by x-ray computed tomography |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9539560/ https://www.ncbi.nlm.nih.gov/pubmed/36212319 http://dx.doi.org/10.3389/fpls.2022.986856 |
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