pyRootHair: Machine learning accelerated software for high-throughput phenotyping of plant root hair traits

Ian Tsang, Lawrence Percival-Alwyn, Stephen Rawsthorne, James Cockram, Fiona Leigh, Jonathan A Atkinson

Open source

DOI
10.1093/gigascience/giaf141
Published
2025-11-13
Container
GigaScience
Publisher
Oxford University Press (OUP)
Open access
unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

Cite this work

BibTeX

@article{allodium:10.1093/gigascience/giaf141,
  title = {pyRootHair: Machine learning accelerated software for high-throughput phenotyping of plant root hair traits},
  author = {Ian Tsang and Lawrence Percival-Alwyn and Stephen Rawsthorne and James Cockram and Fiona Leigh and Jonathan A Atkinson},
  year = {2025},
  journal = {GigaScience},
  doi = {10.1093/gigascience/giaf141},
  url = {https://doi.org/10.1093/gigascience/giaf141}
}

RIS

TY  - JOUR
TI  - pyRootHair: Machine learning accelerated software for high-throughput phenotyping of plant root hair traits
AU  - Ian Tsang
AU  - Lawrence Percival-Alwyn
AU  - Stephen Rawsthorne
AU  - James Cockram
AU  - Fiona Leigh
AU  - Jonathan A Atkinson
PY  - 2025
JO  - GigaScience
DO  - 10.1093/gigascience/giaf141
UR  - https://doi.org/10.1093/gigascience/giaf141
ER  - 

APA

Tsang, I., Percival-Alwyn, L., Rawsthorne, S., Cockram, J., Leigh, F., & Atkinson, J. A. (2025). pyRootHair: Machine learning accelerated software for high-throughput phenotyping of plant root hair traits. GigaScience. https://doi.org/10.1093/gigascience/giaf141

Source records