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Workflow for phenotyping sugar beet roots by automated evaluation of cell characteristics and tissue arrangement using digital image processing

BACKGROUND: Cell characteristics, including cell type, size, shape, packing, cell-to-cell-adhesion, intercellular space, and cell wall thickness, influence the physical characteristics of plant tissues. Genotypic differences were found concerning damage susceptibility related to beet texture for sug...

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Autores principales: Nause, Nelia, Ispizua Yamati, Facundo R., Seidel, Marion, Mahlein, Anne-Katrin, Hoffmann, Christa M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10064576/
https://www.ncbi.nlm.nih.gov/pubmed/37004019
http://dx.doi.org/10.1186/s13007-023-01014-0
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author Nause, Nelia
Ispizua Yamati, Facundo R.
Seidel, Marion
Mahlein, Anne-Katrin
Hoffmann, Christa M.
author_facet Nause, Nelia
Ispizua Yamati, Facundo R.
Seidel, Marion
Mahlein, Anne-Katrin
Hoffmann, Christa M.
author_sort Nause, Nelia
collection PubMed
description BACKGROUND: Cell characteristics, including cell type, size, shape, packing, cell-to-cell-adhesion, intercellular space, and cell wall thickness, influence the physical characteristics of plant tissues. Genotypic differences were found concerning damage susceptibility related to beet texture for sugar beet (Beta vulgaris). Sugar beet storage roots are characterized by heterogeneous tissue with several cambium rings surrounded by small-celled vascular tissue and big-celled sugar-storing parenchyma between the rings. This study presents a procedure for phenotyping heterogeneous tissues like beetroots by imaging. RESULTS: Ten Beta genotypes (nine sugar beet and one fodder beet) were included to establish a pipeline for the automated histologic evaluation of cell characteristics and tissue arrangement using digital image processing written in the programming language R. The identification of cells has been validated by comparison with manual cell identification. Cells are reliably discriminated from intercellular spaces, and cells with similar morphological features are assigned to biological tissue types. CONCLUSIONS: Genotypic differences in cell diameter and cell arrangement can straightforwardly be phenotyped by the presented workflow. The presented routine can further identify genotypic differences in cell diameter and cell arrangement during early growth stages and between sugar storage capabilities. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13007-023-01014-0.
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spelling pubmed-100645762023-04-01 Workflow for phenotyping sugar beet roots by automated evaluation of cell characteristics and tissue arrangement using digital image processing Nause, Nelia Ispizua Yamati, Facundo R. Seidel, Marion Mahlein, Anne-Katrin Hoffmann, Christa M. Plant Methods Methodology BACKGROUND: Cell characteristics, including cell type, size, shape, packing, cell-to-cell-adhesion, intercellular space, and cell wall thickness, influence the physical characteristics of plant tissues. Genotypic differences were found concerning damage susceptibility related to beet texture for sugar beet (Beta vulgaris). Sugar beet storage roots are characterized by heterogeneous tissue with several cambium rings surrounded by small-celled vascular tissue and big-celled sugar-storing parenchyma between the rings. This study presents a procedure for phenotyping heterogeneous tissues like beetroots by imaging. RESULTS: Ten Beta genotypes (nine sugar beet and one fodder beet) were included to establish a pipeline for the automated histologic evaluation of cell characteristics and tissue arrangement using digital image processing written in the programming language R. The identification of cells has been validated by comparison with manual cell identification. Cells are reliably discriminated from intercellular spaces, and cells with similar morphological features are assigned to biological tissue types. CONCLUSIONS: Genotypic differences in cell diameter and cell arrangement can straightforwardly be phenotyped by the presented workflow. The presented routine can further identify genotypic differences in cell diameter and cell arrangement during early growth stages and between sugar storage capabilities. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13007-023-01014-0. BioMed Central 2023-03-31 /pmc/articles/PMC10064576/ /pubmed/37004019 http://dx.doi.org/10.1186/s13007-023-01014-0 Text en © The Author(s) 2023 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
Nause, Nelia
Ispizua Yamati, Facundo R.
Seidel, Marion
Mahlein, Anne-Katrin
Hoffmann, Christa M.
Workflow for phenotyping sugar beet roots by automated evaluation of cell characteristics and tissue arrangement using digital image processing
title Workflow for phenotyping sugar beet roots by automated evaluation of cell characteristics and tissue arrangement using digital image processing
title_full Workflow for phenotyping sugar beet roots by automated evaluation of cell characteristics and tissue arrangement using digital image processing
title_fullStr Workflow for phenotyping sugar beet roots by automated evaluation of cell characteristics and tissue arrangement using digital image processing
title_full_unstemmed Workflow for phenotyping sugar beet roots by automated evaluation of cell characteristics and tissue arrangement using digital image processing
title_short Workflow for phenotyping sugar beet roots by automated evaluation of cell characteristics and tissue arrangement using digital image processing
title_sort workflow for phenotyping sugar beet roots by automated evaluation of cell characteristics and tissue arrangement using digital image processing
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10064576/
https://www.ncbi.nlm.nih.gov/pubmed/37004019
http://dx.doi.org/10.1186/s13007-023-01014-0
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