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DIRT/3D: 3D root phenotyping for field-grown maize (Zea mays)

The development of crops with deeper roots holds substantial promise to mitigate the consequences of climate change. Deeper roots are an essential factor to improve water uptake as a way to enhance crop resilience to drought, to increase nitrogen capture, to reduce fertilizer inputs, and to increase...

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Detalles Bibliográficos
Autores principales: Liu, Suxing, Barrow, Carlos Sherard, Hanlon, Meredith, Lynch, Jonathan P., Bucksch, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8491025/
https://www.ncbi.nlm.nih.gov/pubmed/34608967
http://dx.doi.org/10.1093/plphys/kiab311
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author Liu, Suxing
Barrow, Carlos Sherard
Hanlon, Meredith
Lynch, Jonathan P.
Bucksch, Alexander
author_facet Liu, Suxing
Barrow, Carlos Sherard
Hanlon, Meredith
Lynch, Jonathan P.
Bucksch, Alexander
author_sort Liu, Suxing
collection PubMed
description The development of crops with deeper roots holds substantial promise to mitigate the consequences of climate change. Deeper roots are an essential factor to improve water uptake as a way to enhance crop resilience to drought, to increase nitrogen capture, to reduce fertilizer inputs, and to increase carbon sequestration from the atmosphere to improve soil organic fertility. A major bottleneck to achieving these improvements is high-throughput phenotyping to quantify root phenotypes of field-grown roots. We address this bottleneck with Digital Imaging of Root Traits (DIRT)/3D, an image-based 3D root phenotyping platform, which measures 18 architecture traits from mature field-grown maize (Zea mays) root crowns (RCs) excavated with the Shovelomics technique. DIRT/3D reliably computed all 18 traits, including distance between whorls and the number, angles, and diameters of nodal roots, on a test panel of 12 contrasting maize genotypes. The computed results were validated through comparison with manual measurements. Overall, we observed a coefficient of determination of [Formula: see text] >0.84 and a high broad-sense heritability of [Formula: see text] > 0.6 for all but one trait. The average values of the 18 traits and a developed descriptor to characterize complete root architecture distinguished all genotypes. DIRT/3D is a step toward automated quantification of highly occluded maize RCs. Therefore, DIRT/3D supports breeders and root biologists in improving carbon sequestration and food security in the face of the adverse effects of climate change.
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spelling pubmed-84910252021-10-06 DIRT/3D: 3D root phenotyping for field-grown maize (Zea mays) Liu, Suxing Barrow, Carlos Sherard Hanlon, Meredith Lynch, Jonathan P. Bucksch, Alexander Plant Physiol Regular Issue The development of crops with deeper roots holds substantial promise to mitigate the consequences of climate change. Deeper roots are an essential factor to improve water uptake as a way to enhance crop resilience to drought, to increase nitrogen capture, to reduce fertilizer inputs, and to increase carbon sequestration from the atmosphere to improve soil organic fertility. A major bottleneck to achieving these improvements is high-throughput phenotyping to quantify root phenotypes of field-grown roots. We address this bottleneck with Digital Imaging of Root Traits (DIRT)/3D, an image-based 3D root phenotyping platform, which measures 18 architecture traits from mature field-grown maize (Zea mays) root crowns (RCs) excavated with the Shovelomics technique. DIRT/3D reliably computed all 18 traits, including distance between whorls and the number, angles, and diameters of nodal roots, on a test panel of 12 contrasting maize genotypes. The computed results were validated through comparison with manual measurements. Overall, we observed a coefficient of determination of [Formula: see text] >0.84 and a high broad-sense heritability of [Formula: see text] > 0.6 for all but one trait. The average values of the 18 traits and a developed descriptor to characterize complete root architecture distinguished all genotypes. DIRT/3D is a step toward automated quantification of highly occluded maize RCs. Therefore, DIRT/3D supports breeders and root biologists in improving carbon sequestration and food security in the face of the adverse effects of climate change. Oxford University Press 2021-07-08 /pmc/articles/PMC8491025/ /pubmed/34608967 http://dx.doi.org/10.1093/plphys/kiab311 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of American Society of Plant Biologists. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Regular Issue
Liu, Suxing
Barrow, Carlos Sherard
Hanlon, Meredith
Lynch, Jonathan P.
Bucksch, Alexander
DIRT/3D: 3D root phenotyping for field-grown maize (Zea mays)
title DIRT/3D: 3D root phenotyping for field-grown maize (Zea mays)
title_full DIRT/3D: 3D root phenotyping for field-grown maize (Zea mays)
title_fullStr DIRT/3D: 3D root phenotyping for field-grown maize (Zea mays)
title_full_unstemmed DIRT/3D: 3D root phenotyping for field-grown maize (Zea mays)
title_short DIRT/3D: 3D root phenotyping for field-grown maize (Zea mays)
title_sort dirt/3d: 3d root phenotyping for field-grown maize (zea mays)
topic Regular Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8491025/
https://www.ncbi.nlm.nih.gov/pubmed/34608967
http://dx.doi.org/10.1093/plphys/kiab311
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