High-throughput Phenotyping of Maize Roots Using Digital Image Analysis

Recent 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 e...

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Main Authors:	Coronado Aleans, Verónica, Barrera Sánchez, Carlos F., Guzmán, Manuel
Format:	Artículo
Language:	Español
Published:	Corporación colombiana de investigación agropecuaria - AGROSAVIA 2024
Subjects:	Genética vegetal y fitomejoramiento - F30 Zea mays Mejoramiento genético Características agronómicas Transitorios http://aims.fao.org/aos/agrovoc/c_8504 http://aims.fao.org/aos/agrovoc/c_11119 http://aims.fao.org/aos/agrovoc/c_210
Online Access:	http://hdl.handle.net/20.500.12324/39197 https://doi.org/10.21930/rcta.vol25_num1_art:3312

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record_format	dspace
institution	Corporación Colombiana de Investigación Agropecuaria
collection	Repositorio AGROSAVIA
language	Español
topic	Genética vegetal y fitomejoramiento - F30 Zea mays Mejoramiento genético Características agronómicas Transitorios http://aims.fao.org/aos/agrovoc/c_8504 http://aims.fao.org/aos/agrovoc/c_11119 http://aims.fao.org/aos/agrovoc/c_210
spellingShingle	Genética vegetal y fitomejoramiento - F30 Zea mays Mejoramiento genético Características agronómicas Transitorios http://aims.fao.org/aos/agrovoc/c_8504 http://aims.fao.org/aos/agrovoc/c_11119 http://aims.fao.org/aos/agrovoc/c_210 Coronado Aleans, Verónica Barrera Sánchez, Carlos F. Guzmán, Manuel High-throughput Phenotyping of Maize Roots Using Digital Image Analysis
description	Recent 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.
format	Artículo
author	Coronado Aleans, Verónica Barrera Sánchez, Carlos F. Guzmán, Manuel
author_facet	Coronado Aleans, Verónica Barrera Sánchez, Carlos F. Guzmán, Manuel
author_sort	Coronado Aleans, Verónica
title	High-throughput Phenotyping of Maize Roots Using Digital Image Analysis
title_short	High-throughput Phenotyping of Maize Roots Using Digital Image Analysis
title_full	High-throughput Phenotyping of Maize Roots Using Digital Image Analysis
title_fullStr	High-throughput Phenotyping of Maize Roots Using Digital Image Analysis
title_full_unstemmed	High-throughput Phenotyping of Maize Roots Using Digital Image Analysis
title_sort	high-throughput phenotyping of maize roots using digital image analysis
publisher	Corporación colombiana de investigación agropecuaria - AGROSAVIA
publishDate	2024
url	http://hdl.handle.net/20.500.12324/39197 https://doi.org/10.21930/rcta.vol25_num1_art:3312
work_keys_str_mv	AT coronadoaleansveronica highthroughputphenotypingofmaizerootsusingdigitalimageanalysis AT barrerasanchezcarlosf highthroughputphenotypingofmaizerootsusingdigitalimageanalysis AT guzmanmanuel highthroughputphenotypingofmaizerootsusingdigitalimageanalysis AT coronadoaleansveronica fenotipadodealtorendimientoderaicesdemaizmedianteanalisisdeimagenesdigitales AT barrerasanchezcarlosf fenotipadodealtorendimientoderaicesdemaizmedianteanalisisdeimagenesdigitales AT guzmanmanuel fenotipadodealtorendimientoderaicesdemaizmedianteanalisisdeimagenesdigitales
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spelling	RepoAGROSAVIA391972024-04-25T03:03:02Z High-throughput Phenotyping of Maize Roots Using Digital Image Analysis Fenotipado de alto rendimiento de raíces de maíz mediante análisis de imágenes digitales Coronado Aleans, Verónica Barrera Sánchez, Carlos F. Guzmán, Manuel Genética vegetal y fitomejoramiento - F30 Zea mays Mejoramiento genético Características agronómicas Transitorios http://aims.fao.org/aos/agrovoc/c_8504 http://aims.fao.org/aos/agrovoc/c_11119 http://aims.fao.org/aos/agrovoc/c_210 Recent 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. 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(2009) Genetic and genomic dissection of maize root development and architecture. Current opinion in Plant Biology, 12(2), 172-177. https://doi.org/10.1016/j.pbi.2008.12.002 Kipp, S., Mistele, B., Baresel, P., & Schmidhalter, U. (2014). High-throughput phenotyping early plant vigour of winter wheat. European Journal of Agronomy. 52, 271-278. https://doi.org/10.1016/j.eja.2013.08.009 Kuijken, P., Van Eeuwijk, A., Marcelis, M., & Bouwmeester, J. (2015). Root phenotyping: from component trait in the lab to breeding. Journal of Experimental Botany, 66(18), 5389k5401. https://doi.org/10.1093/jxb/erv239 Le Marié, C. A., York, L. M., Strigens, A., Heinz, C., Giuliani, S., Lynch, J., & Hund, A. (2019). Shovelomics root traits assessed on the EURoot maize panel are highly heritable across environments but show low genotype-by-nitrogen interaction. Euphytica, 215(10), 173. https://doi.org/10.1007/s10681-019-2472-8 Liu, J., & Pattey, E. (2010). 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Annals of Botany, 112(2), 381-38. https://doi.org/10.1093/aob/mcs245 York, L. M., & Lynch, J. P. (2015). Intensive field phenotyping of maize (Zea mays L.) root crowns identifies phenes and phene integration associated with plant growth and nitrogen acquisition. Journal of Experimental Botany, 66(18), 5493-5505. https://doi.org/10.1093/jxb/erv241 York, L. M., Nord, E. A. Lynch, J. P. (2013). Integration of root phenes for soil resource acquisition. Frontiers in Plant Science, 4, 355. https://doi.org/10.3389/fpls.2013.00355 Zhan, A., & Lynch, J. P. (2015). Reduced frequency of lateral root branching improves N capture from low-N soils in maize. Journal of Experimental Botany, 66(7), 2055-2065. https://doi.org/10.1093/jxb/erv007 Zhang, C., Postma, J. A., York, L. M., Lynch, J. P. (2014). Root foraging elicits niche complementarity-dependent yield advantage in the ancient ‘three sisters’ (maize/bean/squash) polyculture, Annals of Botany, 114(8), 1719-1733. https://doi.org/10.1093/aob/mcu191 Attribution-NonCommercial-ShareAlike 4.0 International http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf application/pdf Colombia Corporación colombiana de investigación agropecuaria - AGROSAVIA Mosquera (Colombia) Ciencia y Tecnología Agropecuaria; Vol 25, Núm.1 (2023): Ciencia y Tecnología Agropecuaria; p. 1-16.

High-throughput Phenotyping of Maize Roots Using Digital Image Analysis

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