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RootGraph: a graphic optimization tool for automated image analysis of plant roots
This paper outlines a numerical scheme for accurate, detailed, and high-throughput image analysis of plant roots. In contrast to existing root image analysis tools that focus on root system-average traits, a novel, fully automated and robust approach for the detailed characterization of root traits,...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4623675/ https://www.ncbi.nlm.nih.gov/pubmed/26224880 http://dx.doi.org/10.1093/jxb/erv359 |
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author | Cai, Jinhai Zeng, Zhanghui Connor, Jason N. Huang, Chun Yuan Melino, Vanessa Kumar, Pankaj Miklavcic, Stanley J. |
author_facet | Cai, Jinhai Zeng, Zhanghui Connor, Jason N. Huang, Chun Yuan Melino, Vanessa Kumar, Pankaj Miklavcic, Stanley J. |
author_sort | Cai, Jinhai |
collection | PubMed |
description | This paper outlines a numerical scheme for accurate, detailed, and high-throughput image analysis of plant roots. In contrast to existing root image analysis tools that focus on root system-average traits, a novel, fully automated and robust approach for the detailed characterization of root traits, based on a graph optimization process is presented. The scheme, firstly, distinguishes primary roots from lateral roots and, secondly, quantifies a broad spectrum of root traits for each identified primary and lateral root. Thirdly, it associates lateral roots and their properties with the specific primary root from which the laterals emerge. The performance of this approach was evaluated through comparisons with other automated and semi-automated software solutions as well as against results based on manual measurements. The comparisons and subsequent application of the algorithm to an array of experimental data demonstrate that this method outperforms existing methods in terms of accuracy, robustness, and the ability to process root images under high-throughput conditions. |
format | Online Article Text |
id | pubmed-4623675 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-46236752015-10-29 RootGraph: a graphic optimization tool for automated image analysis of plant roots Cai, Jinhai Zeng, Zhanghui Connor, Jason N. Huang, Chun Yuan Melino, Vanessa Kumar, Pankaj Miklavcic, Stanley J. J Exp Bot Research Paper This paper outlines a numerical scheme for accurate, detailed, and high-throughput image analysis of plant roots. In contrast to existing root image analysis tools that focus on root system-average traits, a novel, fully automated and robust approach for the detailed characterization of root traits, based on a graph optimization process is presented. The scheme, firstly, distinguishes primary roots from lateral roots and, secondly, quantifies a broad spectrum of root traits for each identified primary and lateral root. Thirdly, it associates lateral roots and their properties with the specific primary root from which the laterals emerge. The performance of this approach was evaluated through comparisons with other automated and semi-automated software solutions as well as against results based on manual measurements. The comparisons and subsequent application of the algorithm to an array of experimental data demonstrate that this method outperforms existing methods in terms of accuracy, robustness, and the ability to process root images under high-throughput conditions. Oxford University Press 2015-09 2015-07-29 /pmc/articles/PMC4623675/ /pubmed/26224880 http://dx.doi.org/10.1093/jxb/erv359 Text en © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology. http://creativecommons.org/licenses/by/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Paper Cai, Jinhai Zeng, Zhanghui Connor, Jason N. Huang, Chun Yuan Melino, Vanessa Kumar, Pankaj Miklavcic, Stanley J. RootGraph: a graphic optimization tool for automated image analysis of plant roots |
title | RootGraph: a graphic optimization tool for automated image analysis of plant roots |
title_full | RootGraph: a graphic optimization tool for automated image analysis of plant roots |
title_fullStr | RootGraph: a graphic optimization tool for automated image analysis of plant roots |
title_full_unstemmed | RootGraph: a graphic optimization tool for automated image analysis of plant roots |
title_short | RootGraph: a graphic optimization tool for automated image analysis of plant roots |
title_sort | rootgraph: a graphic optimization tool for automated image analysis of plant roots |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4623675/ https://www.ncbi.nlm.nih.gov/pubmed/26224880 http://dx.doi.org/10.1093/jxb/erv359 |
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