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Modeling root system growth around obstacles
State-of-the-Art models of Root System Architecture (RSA) do not allow simulating root growth around rigid obstacles. Yet, the presence of obstacles can be highly disruptive to the root system. We grew wheat seedlings in sealed petri dishes without obstacle and in custom 3D-printed rhizoboxes contai...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7522252/ https://www.ncbi.nlm.nih.gov/pubmed/32985531 http://dx.doi.org/10.1038/s41598-020-72557-8 |
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author | Jin, Wencheng Aufrecht, Jayde Patino-Ramirez, Fernando Cabral, Heidy Arson, Chloé Retterer, Scott T. |
author_facet | Jin, Wencheng Aufrecht, Jayde Patino-Ramirez, Fernando Cabral, Heidy Arson, Chloé Retterer, Scott T. |
author_sort | Jin, Wencheng |
collection | PubMed |
description | State-of-the-Art models of Root System Architecture (RSA) do not allow simulating root growth around rigid obstacles. Yet, the presence of obstacles can be highly disruptive to the root system. We grew wheat seedlings in sealed petri dishes without obstacle and in custom 3D-printed rhizoboxes containing obstacles. Time-lapse photography was used to reconstruct the wheat root morphology network. We used the reconstructed wheat root network without obstacle to calibrate an RSA model implemented in the R-SWMS software. The root network with obstacles allowed calibrating the parameters of a new function that models the influence of rigid obstacles on wheat root growth. Experimental results show that the presence of a rigid obstacle does not affect the growth rate of the wheat root axes, but that it does influence the root trajectory after the main axis has passed the obstacle. The growth recovery time, i.e. the time for the main root axis to recover its geotropism-driven growth, is proportional to the time during which the main axis grows along the obstacle. Qualitative and quantitative comparisons between experimental and numerical results show that the proposed model successfully simulates wheat RSA growth around obstacles. Our results suggest that wheat roots follow patterns that could inspire the design of adaptive engineering flow networks. |
format | Online Article Text |
id | pubmed-7522252 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-75222522020-09-29 Modeling root system growth around obstacles Jin, Wencheng Aufrecht, Jayde Patino-Ramirez, Fernando Cabral, Heidy Arson, Chloé Retterer, Scott T. Sci Rep Article State-of-the-Art models of Root System Architecture (RSA) do not allow simulating root growth around rigid obstacles. Yet, the presence of obstacles can be highly disruptive to the root system. We grew wheat seedlings in sealed petri dishes without obstacle and in custom 3D-printed rhizoboxes containing obstacles. Time-lapse photography was used to reconstruct the wheat root morphology network. We used the reconstructed wheat root network without obstacle to calibrate an RSA model implemented in the R-SWMS software. The root network with obstacles allowed calibrating the parameters of a new function that models the influence of rigid obstacles on wheat root growth. Experimental results show that the presence of a rigid obstacle does not affect the growth rate of the wheat root axes, but that it does influence the root trajectory after the main axis has passed the obstacle. The growth recovery time, i.e. the time for the main root axis to recover its geotropism-driven growth, is proportional to the time during which the main axis grows along the obstacle. Qualitative and quantitative comparisons between experimental and numerical results show that the proposed model successfully simulates wheat RSA growth around obstacles. Our results suggest that wheat roots follow patterns that could inspire the design of adaptive engineering flow networks. Nature Publishing Group UK 2020-09-28 /pmc/articles/PMC7522252/ /pubmed/32985531 http://dx.doi.org/10.1038/s41598-020-72557-8 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Jin, Wencheng Aufrecht, Jayde Patino-Ramirez, Fernando Cabral, Heidy Arson, Chloé Retterer, Scott T. Modeling root system growth around obstacles |
title | Modeling root system growth around obstacles |
title_full | Modeling root system growth around obstacles |
title_fullStr | Modeling root system growth around obstacles |
title_full_unstemmed | Modeling root system growth around obstacles |
title_short | Modeling root system growth around obstacles |
title_sort | modeling root system growth around obstacles |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7522252/ https://www.ncbi.nlm.nih.gov/pubmed/32985531 http://dx.doi.org/10.1038/s41598-020-72557-8 |
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