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Open source 3D phenotyping of chickpea plant architecture across plant development

BACKGROUND: Being able to accurately assess the 3D architecture of plant canopies can allow us to better estimate plant productivity and improve our understanding of underlying plant processes. This is especially true if we can monitor these traits across plant development. Photogrammetry techniques...

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Autores principales: Salter, William T., Shrestha, Arjina, Barbour, Margaret M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8444385/
https://www.ncbi.nlm.nih.gov/pubmed/34530876
http://dx.doi.org/10.1186/s13007-021-00795-6
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author Salter, William T.
Shrestha, Arjina
Barbour, Margaret M.
author_facet Salter, William T.
Shrestha, Arjina
Barbour, Margaret M.
author_sort Salter, William T.
collection PubMed
description BACKGROUND: Being able to accurately assess the 3D architecture of plant canopies can allow us to better estimate plant productivity and improve our understanding of underlying plant processes. This is especially true if we can monitor these traits across plant development. Photogrammetry techniques, such as structure from motion, have been shown to provide accurate 3D reconstructions of monocot crop species such as wheat and rice, yet there has been little success reconstructing crop species with smaller leaves and more complex branching architectures, such as chickpea. RESULTS: In this work, we developed a low-cost 3D scanner and used an open-source data processing pipeline to assess the 3D structure of individual chickpea plants. The imaging system we developed consists of a user programmable turntable and three cameras that automatically captures 120 images of each plant and offloads these to a computer for processing. The capture process takes 5–10 min for each plant and the majority of the reconstruction process on a Windows PC is automated. Plant height and total plant surface area were validated against “ground truth” measurements, producing R(2) > 0.99 and a mean absolute percentage error < 10%. We demonstrate the ability to assess several important architectural traits, including canopy volume and projected area, and estimate relative growth rate in commercial chickpea cultivars and lines from local and international breeding collections. Detailed analysis of individual reconstructions also allowed us to investigate partitioning of plant surface area, and by proxy plant biomass. CONCLUSIONS: Our results show that it is possible to use low-cost photogrammetry techniques to accurately reconstruct individual chickpea plants, a crop with a complex architecture consisting of many small leaves and a highly branching structure. We hope that our use of open-source software and low-cost hardware will encourage others to use this promising technique for more architecturally complex species. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13007-021-00795-6.
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spelling pubmed-84443852021-09-16 Open source 3D phenotyping of chickpea plant architecture across plant development Salter, William T. Shrestha, Arjina Barbour, Margaret M. Plant Methods Methodology BACKGROUND: Being able to accurately assess the 3D architecture of plant canopies can allow us to better estimate plant productivity and improve our understanding of underlying plant processes. This is especially true if we can monitor these traits across plant development. Photogrammetry techniques, such as structure from motion, have been shown to provide accurate 3D reconstructions of monocot crop species such as wheat and rice, yet there has been little success reconstructing crop species with smaller leaves and more complex branching architectures, such as chickpea. RESULTS: In this work, we developed a low-cost 3D scanner and used an open-source data processing pipeline to assess the 3D structure of individual chickpea plants. The imaging system we developed consists of a user programmable turntable and three cameras that automatically captures 120 images of each plant and offloads these to a computer for processing. The capture process takes 5–10 min for each plant and the majority of the reconstruction process on a Windows PC is automated. Plant height and total plant surface area were validated against “ground truth” measurements, producing R(2) > 0.99 and a mean absolute percentage error < 10%. We demonstrate the ability to assess several important architectural traits, including canopy volume and projected area, and estimate relative growth rate in commercial chickpea cultivars and lines from local and international breeding collections. Detailed analysis of individual reconstructions also allowed us to investigate partitioning of plant surface area, and by proxy plant biomass. CONCLUSIONS: Our results show that it is possible to use low-cost photogrammetry techniques to accurately reconstruct individual chickpea plants, a crop with a complex architecture consisting of many small leaves and a highly branching structure. We hope that our use of open-source software and low-cost hardware will encourage others to use this promising technique for more architecturally complex species. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13007-021-00795-6. BioMed Central 2021-09-16 /pmc/articles/PMC8444385/ /pubmed/34530876 http://dx.doi.org/10.1186/s13007-021-00795-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Methodology
Salter, William T.
Shrestha, Arjina
Barbour, Margaret M.
Open source 3D phenotyping of chickpea plant architecture across plant development
title Open source 3D phenotyping of chickpea plant architecture across plant development
title_full Open source 3D phenotyping of chickpea plant architecture across plant development
title_fullStr Open source 3D phenotyping of chickpea plant architecture across plant development
title_full_unstemmed Open source 3D phenotyping of chickpea plant architecture across plant development
title_short Open source 3D phenotyping of chickpea plant architecture across plant development
title_sort open source 3d phenotyping of chickpea plant architecture across plant development
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8444385/
https://www.ncbi.nlm.nih.gov/pubmed/34530876
http://dx.doi.org/10.1186/s13007-021-00795-6
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