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archiDART v3.0: A new data analysis pipeline allowing the topological analysis of plant root systems

Quantifying plant morphology is a very challenging task that requires methods able to capture the geometry and topology of plant organs at various spatial scales. Recently, the use of persistent homology as a mathematical framework to quantify plant morphology has been successfully demonstrated for...

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Detalles Bibliográficos
Autores principales: Delory, Benjamin M., Li, Mao, Topp, Christopher N., Lobet, Guillaume
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5871803/
https://www.ncbi.nlm.nih.gov/pubmed/29636899
http://dx.doi.org/10.12688/f1000research.13541.1
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author Delory, Benjamin M.
Li, Mao
Topp, Christopher N.
Lobet, Guillaume
author_facet Delory, Benjamin M.
Li, Mao
Topp, Christopher N.
Lobet, Guillaume
author_sort Delory, Benjamin M.
collection PubMed
description Quantifying plant morphology is a very challenging task that requires methods able to capture the geometry and topology of plant organs at various spatial scales. Recently, the use of persistent homology as a mathematical framework to quantify plant morphology has been successfully demonstrated for leaves, shoots, and root systems. In this paper, we present a new data analysis pipeline implemented in the R package archiDART to analyse root system architectures using persistent homology. In addition, we also show that both geometric and topological descriptors are necessary to accurately compare root systems and assess their natural complexity.
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spelling pubmed-58718032018-04-09 archiDART v3.0: A new data analysis pipeline allowing the topological analysis of plant root systems Delory, Benjamin M. Li, Mao Topp, Christopher N. Lobet, Guillaume F1000Res Software Tool Article Quantifying plant morphology is a very challenging task that requires methods able to capture the geometry and topology of plant organs at various spatial scales. Recently, the use of persistent homology as a mathematical framework to quantify plant morphology has been successfully demonstrated for leaves, shoots, and root systems. In this paper, we present a new data analysis pipeline implemented in the R package archiDART to analyse root system architectures using persistent homology. In addition, we also show that both geometric and topological descriptors are necessary to accurately compare root systems and assess their natural complexity. F1000 Research Limited 2018-01-08 /pmc/articles/PMC5871803/ /pubmed/29636899 http://dx.doi.org/10.12688/f1000research.13541.1 Text en Copyright: © 2018 Delory BM et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software Tool Article
Delory, Benjamin M.
Li, Mao
Topp, Christopher N.
Lobet, Guillaume
archiDART v3.0: A new data analysis pipeline allowing the topological analysis of plant root systems
title archiDART v3.0: A new data analysis pipeline allowing the topological analysis of plant root systems
title_full archiDART v3.0: A new data analysis pipeline allowing the topological analysis of plant root systems
title_fullStr archiDART v3.0: A new data analysis pipeline allowing the topological analysis of plant root systems
title_full_unstemmed archiDART v3.0: A new data analysis pipeline allowing the topological analysis of plant root systems
title_short archiDART v3.0: A new data analysis pipeline allowing the topological analysis of plant root systems
title_sort archidart v3.0: a new data analysis pipeline allowing the topological analysis of plant root systems
topic Software Tool Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5871803/
https://www.ncbi.nlm.nih.gov/pubmed/29636899
http://dx.doi.org/10.12688/f1000research.13541.1
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