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

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...

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Main Authors: Dupoy, 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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Published: BioMed Central 2017
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Online Access:https://eprints.nottingham.ac.uk/44225/
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author Dupoy, 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.
author_facet Dupoy, 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.
author_sort Dupoy, Lionel X.
building Nottingham Research Data Repository
collection Online Access
description 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.
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spelling nottingham-442252020-05-04T18:55:09Z https://eprints.nottingham.ac.uk/44225/ Accelerating root system phenotyping of seedlings through a computer‑assisted processing pipeline Dupoy, 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. 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. BioMed Central 2017-07-13 Article PeerReviewed Dupoy, 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. and White, Philip J. (2017) Accelerating root system phenotyping of seedlings through a computer‑assisted processing pipeline. Plant Methods, 13 (57). pp. 1-14. ISSN 1746-4811 Root Phenotyping Error Pipeline Barley Brassica https://plantmethods.biomedcentral.com/articles/10.1186/s13007-017-0207-1 doi:10.1186/s13007-017-0207-1 doi:10.1186/s13007-017-0207-1
spellingShingle Root
Phenotyping
Error
Pipeline
Barley
Brassica
Dupoy, 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.
Accelerating root system phenotyping of seedlings through a computer‑assisted processing pipeline
title Accelerating root system phenotyping of seedlings through a computer‑assisted processing pipeline
title_full Accelerating root system phenotyping of seedlings through a computer‑assisted processing pipeline
title_fullStr Accelerating root system phenotyping of seedlings through a computer‑assisted processing pipeline
title_full_unstemmed Accelerating root system phenotyping of seedlings through a computer‑assisted processing pipeline
title_short Accelerating root system phenotyping of seedlings through a computer‑assisted processing pipeline
title_sort accelerating root system phenotyping of seedlings through a computer‑assisted processing pipeline
topic Root
Phenotyping
Error
Pipeline
Barley
Brassica
url https://eprints.nottingham.ac.uk/44225/
https://eprints.nottingham.ac.uk/44225/
https://eprints.nottingham.ac.uk/44225/