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Accelerating root system phenotyping of seedlings through a computer‑assisted processing pipeline

Dupuy, Lionel X.; Wright, Gladys; Thompson, Jacqueline A.; Taylor, Anna; Dekeyser, Sebastien; White, Christopher P.; Thomas, Wiliam T.B.; Nightingale, Mark; Hammond, John P.; Graham, Neil S.; Thomas, Catherine L.; Broadley, Martin R.; White, Philip J.

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Authors

Lionel X. Dupuy

Gladys Wright

Jacqueline A. Thompson

Anna Taylor

Sebastien Dekeyser

Christopher P. White

Wiliam T.B. Thomas

Mark Nightingale

John P. Hammond

NEIL GRAHAM NEIL.GRAHAM@NOTTINGHAM.AC.UK
Senior Research Fellow

Catherine L. Thomas

Philip J. White



Abstract

Background: There are numerous systems and techniques to measure the growth of plant roots. However, phenotyping large numbers of plant roots for breeding and genetic analyses remains challenging. One major difficulty is to achieve high throughput and resolution at a reasonable cost per plant sample. Here we describe a cost-effective root phenotyping pipeline, on which we perform time and accuracy benchmarking to identify bottlenecks in such pipelines and strategies for their acceleration.
Results: Our root phenotyping pipeline was assembled with custom software and low cost material and equipment. Results show that sample preparation and handling of samples during screening are the most time consuming task in root phenotyping. Algorithms can be used to speed up the extraction of root traits from image data, but when applied to large numbers of images, there is a trade-off between time of processing the data and errors contained in the database.
Conclusions: Scaling-up root phenotyping to large numbers of genotypes will require not only automation of sample preparation and sample handling, but also efficient algorithms for error detection for more reliable replacement of manual interventions.

Citation

Dupuy, L. X., Wright, G., Thompson, J. A., Taylor, A., Dekeyser, S., White, C. P., …White, P. J. (2017). Accelerating root system phenotyping of seedlings through a computer‑assisted processing pipeline. Plant Methods, 13(1), Article 57. https://doi.org/10.1186/s13007-017-0207-1

Journal Article Type Article
Acceptance Date Jul 4, 2017
Online Publication Date Jul 13, 2017
Publication Date 2017-12
Deposit Date Jul 17, 2017
Publicly Available Date Jul 17, 2017
Journal Plant Methods
Electronic ISSN 1746-4811
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 13
Issue 1
Article Number 57
DOI https://doi.org/10.1186/s13007-017-0207-1
Keywords Root, Phenotyping, Error, Pipeline, Barley, Brassica
Public URL https://nottingham-repository.worktribe.com/output/872322
Publisher URL https://plantmethods.biomedcentral.com/articles/10.1186/s13007-017-0207-1
Related Public URLs https://creativecommons.org/licenses/by/4.0/
Contract Date Jul 17, 2017

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