Literature DB >> 34608967

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

Suxing Liu1,2,3, Carlos Sherard Barrow4, Meredith Hanlon5, Jonathan P Lynch5, Alexander Bucksch1,2,3.   

Abstract

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 r2>0.84 and a high broad-sense heritability of Hmean2> 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.
© The Author(s) 2021. Published by Oxford University Press on behalf of American Society of Plant Biologists.

Entities:  

Mesh:

Year:  2021        PMID: 34608967      PMCID: PMC8491025          DOI: 10.1093/plphys/kiab311

Source DB:  PubMed          Journal:  Plant Physiol        ISSN: 0032-0889            Impact factor:   8.340


  59 in total

1.  Shovelomics for phenotyping root architectural traits of rapeseed/canola (Brassica napus L.) and genome-wide association mapping.

Authors:  Muhammad Arifuzzaman; Atena Oladzadabbasabadi; Phillip McClean; Mukhlesur Rahman
Journal:  Mol Genet Genomics       Date:  2019-04-09       Impact factor: 3.291

2.  From lab to field, new approaches to phenotyping root system architecture.

Authors:  Jinming Zhu; Paul A Ingram; Philip N Benfey; Tedd Elich
Journal:  Curr Opin Plant Biol       Date:  2011-04-27       Impact factor: 7.834

Review 3.  Pampered inside, pestered outside? Differences and similarities between plants growing in controlled conditions and in the field.

Authors:  Hendrik Poorter; Fabio Fiorani; Roland Pieruschka; Tobias Wojciechowski; Wim H van der Putten; Michael Kleyer; Uli Schurr; Johannes Postma
Journal:  New Phytol       Date:  2016-10-26       Impact factor: 10.151

Review 4.  How can we harness quantitative genetic variation in crop root systems for agricultural improvement?

Authors:  Christopher N Topp; Adam L Bray; Nathanael A Ellis; Zhengbin Liu
Journal:  J Integr Plant Biol       Date:  2016-03-11       Impact factor: 7.061

5.  Three-Dimensional Time-Lapse Analysis Reveals Multiscale Relationships in Maize Root Systems with Contrasting Architectures.

Authors:  Ni Jiang; Eric Floro; Adam L Bray; Benjamin Laws; Keith E Duncan; Christopher N Topp
Journal:  Plant Cell       Date:  2019-05-23       Impact factor: 11.277

6.  RooTrak: automated recovery of three-dimensional plant root architecture in soil from x-ray microcomputed tomography images using visual tracking.

Authors:  Stefan Mairhofer; Susan Zappala; Saoirse R Tracy; Craig Sturrock; Malcolm Bennett; Sacha J Mooney; Tony Pridmore
Journal:  Plant Physiol       Date:  2011-12-21       Impact factor: 8.340

7.  Shared Genetic Control of Root System Architecture between Zea mays and Sorghum bicolor.

Authors:  Zihao Zheng; Stefan Hey; Talukder Jubery; Huyu Liu; Yu Yang; Lisa Coffey; Chenyong Miao; Brandi Sigmon; James C Schnable; Frank Hochholdinger; Baskar Ganapathysubramanian; Patrick S Schnable
Journal:  Plant Physiol       Date:  2019-11-18       Impact factor: 8.340

8.  Affordable and robust phenotyping framework to analyse root system architecture of soil-grown plants.

Authors:  Thibaut Bontpart; Cristobal Concha; Mario Valerio Giuffrida; Ingrid Robertson; Kassahun Admkie; Tulu Degefu; Nigusie Girma; Kassahun Tesfaye; Teklehaimanot Haileselassie; Asnake Fikre; Masresha Fetene; Sotirios A Tsaftaris; Peter Doerner
Journal:  Plant J       Date:  2020-07-15       Impact factor: 6.417

9.  Low crown root number enhances nitrogen acquisition from low-nitrogen soils in maize.

Authors:  Patompong Saengwilai; Xiaoli Tian; Jonathan Paul Lynch
Journal:  Plant Physiol       Date:  2014-04-04       Impact factor: 8.340

10.  Direct comparison of MRI and X-ray CT technologies for 3D imaging of root systems in soil: potential and challenges for root trait quantification.

Authors:  Ralf Metzner; Anja Eggert; Dagmar van Dusschoten; Daniel Pflugfelder; Stefan Gerth; Ulrich Schurr; Norman Uhlmann; Siegfried Jahnke
Journal:  Plant Methods       Date:  2015-03-11       Impact factor: 4.993

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  3 in total

1.  TopoRoot: a method for computing hierarchy and fine-grained traits of maize roots from 3D imaging.

Authors:  Dan Zeng; Mao Li; Ni Jiang; Yiwen Ju; Hannah Schreiber; Erin Chambers; David Letscher; Tao Ju; Christopher N Topp
Journal:  Plant Methods       Date:  2021-12-13       Impact factor: 4.993

2.  RhizoPot platform: A high-throughput in situ root phenotyping platform with integrated hardware and software.

Authors:  Hongjuan Zhao; Nan Wang; Hongchun Sun; Lingxiao Zhu; Ke Zhang; Yongjiang Zhang; Jijie Zhu; Anchang Li; Zhiying Bai; Xiaoqing Liu; Hezhong Dong; Liantao Liu; Cundong Li
Journal:  Front Plant Sci       Date:  2022-09-29       Impact factor: 6.627

3.  4DRoot: Root phenotyping software for temporal 3D scans by X-ray computed tomography.

Authors:  Monica Herrero-Huerta; Pasi Raumonen; Diego Gonzalez-Aguilera
Journal:  Front Plant Sci       Date:  2022-09-23       Impact factor: 6.627

  3 in total

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