High-throughput Phenotyping of Maize Roots Using Digital Image Analysis

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dc.audienceInvestigador
dc.coverageSede Central
dc.coverageColombia
dc.creatorCoronado Aleans, Verónica
dc.creatorBarrera Sánchez, Carlos Felipe
dc.creatorGuzmán, Manuel
dc.date2024-04-24T15:42:19Z
dc.date2024-04-24T15:42:19Z
dc.date2024
dc.date2024
dc.date.accessioned2026-06-27T04:41:49Z
dc.descriptionRecent research on maize root architecture has made significant progress, but further research is needed to optimize methods for efficient and accurate acquisition of root architecture data. This study aimed to assess the effectiveness of digital imaging for root phenotyping of Zea mays L. Field experiments were carried out at two locations in the province of Antioquia, Colombia, in 2019 and 2020 to analyze root architecture variables of 12 genotypes of maize. Two methodologies were used: manual phenotyping and digital image analysis. Pearson’s correlation coefficients among variables were estimated. Principal Component Analysis (PCA) was used to summarize and uncover clustering patterns in the multivariate data set. The results indicated correlations between diameter (r = 0.94) and manually measured root diameter. The manually measured right and left root angles correlated with image-derived root angle at r = 0.92 and 0.88, respectively, and root length at r = 0.62. The PCA highlighted that the digital method explained the highest proportion of variation in root areas and diameters, while the manual method dominated in root angle variables. These results corroborate a feasible method to optimize root architecture phenotyping for research questions. This protocol can be adopted under the automatic analysis with REST software for acquiring images of variables associated with roots’ angle, length, and diameter.
dc.descriptionMaíz
dc.descriptionZea mays
dc.formatapplication/pdf
dc.formatapplication/pdf
dc.identifier2500-5308
dc.identifier2500-5308
dc.identifierhttp://hdl.handle.net/20.500.12324/39197
dc.identifierhttps://doi.org/10.21930/rcta.vol25_num1_art:3312
dc.identifierreponame:Biblioteca Digital Agropecuaria de Colombia
dc.identifierinstname:Corporación colombiana de investigación agropecuaria AGROSAVIA
dc.identifier.urihttp://hdl.handle.net/123456789/35697
dc.languagespa
dc.publisherCorporación colombiana de investigación agropecuaria - AGROSAVIA
dc.relationCiencia y Tecnología Agropecuaria
dc.relation25
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dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.sourceCiencia y Tecnología Agropecuaria; Vol 25, Núm.1 (2023): Ciencia y Tecnología Agropecuaria; p. 1-16.
dc.subjectGenética vegetal y fitomejoramiento - F30
dc.subjectZea mays
dc.subjectMejoramiento genético
dc.subjectCaracterísticas agronómicas
dc.subjectTransitorios
dc.subjecthttp://aims.fao.org/aos/agrovoc/c_8504
dc.subjecthttp://aims.fao.org/aos/agrovoc/c_11119
dc.subjecthttp://aims.fao.org/aos/agrovoc/c_210
dc.thumbnailhttps://repository.agrosavia.co/bitstreams/ebfda214-6e79-4e79-8740-b865652e0f51/download
dc.titleHigh-throughput Phenotyping of Maize Roots Using Digital Image Analysis
dc.titleFenotipado de alto rendimiento de raíces de maíz mediante análisis de imágenes digitales
dc.typeArtículo científico

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