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Resumen
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 [ver mas...]
dc.contributor.authorManacorda, Carlos Augusto
dc.contributor.authorAsurmendi, Sebastian
dc.date.accessioned2018-10-18T18:36:20Z
dc.date.available2018-10-18T18:36:20Z
dc.date.issued2018-07
dc.identifier.issn2047-217X
dc.identifier.otherhttps://doi.org/10.1093/gigascience/giy073
dc.identifier.urihttps://academic.oup.com/gigascience/article/7/7/giy073/5039702
dc.identifier.urihttp://hdl.handle.net/20.500.12123/3637
dc.description.abstractBackground: 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.eng
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.publisherOxford University Presses_AR
dc.relationinfo:eu-repograntAgreement/INTA/PNBIO/1131022/AR./Genómica funcional y biología de sistemas.es_AR
dc.rightsinfo:eu-repo/semantics/openAccesses_AR
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.sourceGigaScience 7 (7) : 1-20 (Julio 2018)es_AR
dc.subjectArabidopsises_AR
dc.subjectPhenotypeseng
dc.subjectFenotiposes_AR
dc.subject.otherGeometric Morphometricseng
dc.subject.otherMorfometría Geométricaes_AR
dc.titleArabidopsis phenotyping through geometric morphometricses_AR
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articlees_AR
dc.typeinfo:eu-repo/semantics/publishedVersiones_AR
dc.rights.licenseCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.description.origenInstituto de Biotecnologíaes_AR
dc.description.filFil: Manacorda, Carlos Augusto. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentinaes_AR
dc.description.filFil: Asurmendi, Sebastian. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentinaes_AR
dc.subtypecientifico


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