Arabidopsis phenotyping through geometric morphometrics
- Autores
- Manacorda, Carlos Augusto; Asurmendi, Sebastian
- Año de publicación
- 2018
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Background: Recently, great technical progress has been achieved in the field of plant phenotyping. High-throughput platforms and the development of improved algorithms for rosette image segmentation make it possible to extract shape and size parameters for genetic, physiological, and environmental studies on a large scale. The development of low-cost phenotyping platforms and freeware resources make it possible to widely expand phenotypic analysis tools for Arabidopsis. However, objective descriptors of shape parameters that could be used independently of the platform and segmentation software used are still lacking, and shape descriptions still rely on ad hoc or even contradictory descriptors, which could make comparisons difficult and perhaps inaccurate. Modern geometric morphometrics is a family of methods in quantitative biology proposed to be the main source of data and analytical tools in the emerging field of phenomics studies. Based on the location of landmarks (corresponding points) over imaged specimens and by combining geometry, multivariate analysis, and powerful statistical techniques, these tools offer the possibility to reproducibly and accurately account for shape variations among groups and measure them in shape distance units. Results: Here, a particular scheme of landmark placement on Arabidopsis rosette images is proposed to study shape variation in viral infection processes. Shape differences between controls and infected plants are quantified throughout the infectious process and visualized. Quantitative comparisons between two unrelated ssRNA+ viruses are shown, and reproducibility issues are assessed. Conclusions: Combined with the newest automated platforms and plant segmentation procedures, geometric morphometric tools could boost phenotypic features extraction and processing in an objective, reproducible manner.
Instituto de Biotecnología
Fil: Manacorda, Carlos Augusto. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina
Fil: Asurmendi, Sebastian. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina - Fuente
- GigaScience 7 (7) : 1-20 (Julio 2018)
- Materia
-
Arabidopsis
Fenotipos
Phenotypes
Geometric Morphometrics
Morfometría Geométrica - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Instituto Nacional de Tecnología Agropecuaria
- OAI Identificador
- oai:localhost:20.500.12123/3637
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Arabidopsis phenotyping through geometric morphometricsManacorda, Carlos AugustoAsurmendi, SebastianArabidopsisFenotiposPhenotypesGeometric MorphometricsMorfometría GeométricaBackground: Recently, great technical progress has been achieved in the field of plant phenotyping. High-throughput platforms and the development of improved algorithms for rosette image segmentation make it possible to extract shape and size parameters for genetic, physiological, and environmental studies on a large scale. The development of low-cost phenotyping platforms and freeware resources make it possible to widely expand phenotypic analysis tools for Arabidopsis. However, objective descriptors of shape parameters that could be used independently of the platform and segmentation software used are still lacking, and shape descriptions still rely on ad hoc or even contradictory descriptors, which could make comparisons difficult and perhaps inaccurate. Modern geometric morphometrics is a family of methods in quantitative biology proposed to be the main source of data and analytical tools in the emerging field of phenomics studies. Based on the location of landmarks (corresponding points) over imaged specimens and by combining geometry, multivariate analysis, and powerful statistical techniques, these tools offer the possibility to reproducibly and accurately account for shape variations among groups and measure them in shape distance units. Results: Here, a particular scheme of landmark placement on Arabidopsis rosette images is proposed to study shape variation in viral infection processes. Shape differences between controls and infected plants are quantified throughout the infectious process and visualized. Quantitative comparisons between two unrelated ssRNA+ viruses are shown, and reproducibility issues are assessed. Conclusions: Combined with the newest automated platforms and plant segmentation procedures, geometric morphometric tools could boost phenotypic features extraction and processing in an objective, reproducible manner.Instituto de BiotecnologíaFil: Manacorda, Carlos Augusto. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; ArgentinaFil: Asurmendi, Sebastian. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaOxford University Press2018-10-18T18:36:20Z2018-10-18T18:36:20Z2018-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://academic.oup.com/gigascience/article/7/7/giy073/5039702http://hdl.handle.net/20.500.12123/36372047-217Xhttps://doi.org/10.1093/gigascience/giy073GigaScience 7 (7) : 1-20 (Julio 2018)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repograntAgreement/INTA/PNBIO/1131022/AR./Genómica funcional y biología de sistemas.info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-09-04T09:47:37Zoai:localhost:20.500.12123/3637instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-09-04 09:47:38.057INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse |
dc.title.none.fl_str_mv |
Arabidopsis phenotyping through geometric morphometrics |
title |
Arabidopsis phenotyping through geometric morphometrics |
spellingShingle |
Arabidopsis phenotyping through geometric morphometrics Manacorda, Carlos Augusto Arabidopsis Fenotipos Phenotypes Geometric Morphometrics Morfometría Geométrica |
title_short |
Arabidopsis phenotyping through geometric morphometrics |
title_full |
Arabidopsis phenotyping through geometric morphometrics |
title_fullStr |
Arabidopsis phenotyping through geometric morphometrics |
title_full_unstemmed |
Arabidopsis phenotyping through geometric morphometrics |
title_sort |
Arabidopsis phenotyping through geometric morphometrics |
dc.creator.none.fl_str_mv |
Manacorda, Carlos Augusto Asurmendi, Sebastian |
author |
Manacorda, Carlos Augusto |
author_facet |
Manacorda, Carlos Augusto Asurmendi, Sebastian |
author_role |
author |
author2 |
Asurmendi, Sebastian |
author2_role |
author |
dc.subject.none.fl_str_mv |
Arabidopsis Fenotipos Phenotypes Geometric Morphometrics Morfometría Geométrica |
topic |
Arabidopsis Fenotipos Phenotypes Geometric Morphometrics Morfometría Geométrica |
dc.description.none.fl_txt_mv |
Background: Recently, great technical progress has been achieved in the field of plant phenotyping. High-throughput platforms and the development of improved algorithms for rosette image segmentation make it possible to extract shape and size parameters for genetic, physiological, and environmental studies on a large scale. The development of low-cost phenotyping platforms and freeware resources make it possible to widely expand phenotypic analysis tools for Arabidopsis. However, objective descriptors of shape parameters that could be used independently of the platform and segmentation software used are still lacking, and shape descriptions still rely on ad hoc or even contradictory descriptors, which could make comparisons difficult and perhaps inaccurate. Modern geometric morphometrics is a family of methods in quantitative biology proposed to be the main source of data and analytical tools in the emerging field of phenomics studies. Based on the location of landmarks (corresponding points) over imaged specimens and by combining geometry, multivariate analysis, and powerful statistical techniques, these tools offer the possibility to reproducibly and accurately account for shape variations among groups and measure them in shape distance units. Results: Here, a particular scheme of landmark placement on Arabidopsis rosette images is proposed to study shape variation in viral infection processes. Shape differences between controls and infected plants are quantified throughout the infectious process and visualized. Quantitative comparisons between two unrelated ssRNA+ viruses are shown, and reproducibility issues are assessed. Conclusions: Combined with the newest automated platforms and plant segmentation procedures, geometric morphometric tools could boost phenotypic features extraction and processing in an objective, reproducible manner. Instituto de Biotecnología Fil: Manacorda, Carlos Augusto. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina Fil: Asurmendi, Sebastian. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina |
description |
Background: Recently, great technical progress has been achieved in the field of plant phenotyping. High-throughput platforms and the development of improved algorithms for rosette image segmentation make it possible to extract shape and size parameters for genetic, physiological, and environmental studies on a large scale. The development of low-cost phenotyping platforms and freeware resources make it possible to widely expand phenotypic analysis tools for Arabidopsis. However, objective descriptors of shape parameters that could be used independently of the platform and segmentation software used are still lacking, and shape descriptions still rely on ad hoc or even contradictory descriptors, which could make comparisons difficult and perhaps inaccurate. Modern geometric morphometrics is a family of methods in quantitative biology proposed to be the main source of data and analytical tools in the emerging field of phenomics studies. Based on the location of landmarks (corresponding points) over imaged specimens and by combining geometry, multivariate analysis, and powerful statistical techniques, these tools offer the possibility to reproducibly and accurately account for shape variations among groups and measure them in shape distance units. Results: Here, a particular scheme of landmark placement on Arabidopsis rosette images is proposed to study shape variation in viral infection processes. Shape differences between controls and infected plants are quantified throughout the infectious process and visualized. Quantitative comparisons between two unrelated ssRNA+ viruses are shown, and reproducibility issues are assessed. Conclusions: Combined with the newest automated platforms and plant segmentation procedures, geometric morphometric tools could boost phenotypic features extraction and processing in an objective, reproducible manner. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-10-18T18:36:20Z 2018-10-18T18:36:20Z 2018-07 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
https://academic.oup.com/gigascience/article/7/7/giy073/5039702 http://hdl.handle.net/20.500.12123/3637 2047-217X https://doi.org/10.1093/gigascience/giy073 |
url |
https://academic.oup.com/gigascience/article/7/7/giy073/5039702 http://hdl.handle.net/20.500.12123/3637 https://doi.org/10.1093/gigascience/giy073 |
identifier_str_mv |
2047-217X |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repograntAgreement/INTA/PNBIO/1131022/AR./Genómica funcional y biología de sistemas. |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Oxford University Press |
publisher.none.fl_str_mv |
Oxford University Press |
dc.source.none.fl_str_mv |
GigaScience 7 (7) : 1-20 (Julio 2018) reponame:INTA Digital (INTA) instname:Instituto Nacional de Tecnología Agropecuaria |
reponame_str |
INTA Digital (INTA) |
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INTA Digital (INTA) |
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Instituto Nacional de Tecnología Agropecuaria |
repository.name.fl_str_mv |
INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria |
repository.mail.fl_str_mv |
tripaldi.nicolas@inta.gob.ar |
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