pyRootHair: Machine learning accelerated software for high-throughput phenotyping of plant root hair traits
- DOI
- 10.1093/gigascience/giaf141
- Published
- 2025-11-13
- Container
- GigaScience
- Publisher
- Oxford University Press (OUP)
- Open access
- unknown
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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
- crossref · retrieved 2026-09-24T23:50:07.047Z