Cargando…
ACORBA: Automated workflow to measure Arabidopsis thaliana root tip angle dynamics
The ability of plants to sense and orient their root growth towards gravity is studied in many laboratories. It is known that manual analysis of image data is subjected to human bias. Several semi-automated tools are available for analysing images from flatbed scanners, but there is no solution to a...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10095971/ https://www.ncbi.nlm.nih.gov/pubmed/37077987 http://dx.doi.org/10.1017/qpb.2022.4 |
_version_ | 1785024208864018432 |
---|---|
author | Serre, Nelson B. C. Fendrych, Matyáš |
author_facet | Serre, Nelson B. C. Fendrych, Matyáš |
author_sort | Serre, Nelson B. C. |
collection | PubMed |
description | The ability of plants to sense and orient their root growth towards gravity is studied in many laboratories. It is known that manual analysis of image data is subjected to human bias. Several semi-automated tools are available for analysing images from flatbed scanners, but there is no solution to automatically measure root bending angle over time for vertical-stage microscopy images. To address these problems, we developed ACORBA, which is an automated software that can measure root bending angle over time from vertical-stage microscope and flatbed scanner images. ACORBA also has a semi-automated mode for camera or stereomicroscope images. It represents a flexible approach based on both traditional image processing and deep machine learning segmentation to measure root angle progression over time. As the software is automated, it limits human interactions and is reproducible. ACORBA will support the plant biologist community by reducing labour and increasing reproducibility of image analysis of root gravitropism. |
format | Online Article Text |
id | pubmed-10095971 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-100959712023-04-18 ACORBA: Automated workflow to measure Arabidopsis thaliana root tip angle dynamics Serre, Nelson B. C. Fendrych, Matyáš Quant Plant Biol Original Research Article The ability of plants to sense and orient their root growth towards gravity is studied in many laboratories. It is known that manual analysis of image data is subjected to human bias. Several semi-automated tools are available for analysing images from flatbed scanners, but there is no solution to automatically measure root bending angle over time for vertical-stage microscopy images. To address these problems, we developed ACORBA, which is an automated software that can measure root bending angle over time from vertical-stage microscope and flatbed scanner images. ACORBA also has a semi-automated mode for camera or stereomicroscope images. It represents a flexible approach based on both traditional image processing and deep machine learning segmentation to measure root angle progression over time. As the software is automated, it limits human interactions and is reproducible. ACORBA will support the plant biologist community by reducing labour and increasing reproducibility of image analysis of root gravitropism. Cambridge University Press 2022-05-24 /pmc/articles/PMC10095971/ /pubmed/37077987 http://dx.doi.org/10.1017/qpb.2022.4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc-sa/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike licence (https://creativecommons.org/licenses/by-nc-sa/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the same Creative Commons licence is included and the original work is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use. |
spellingShingle | Original Research Article Serre, Nelson B. C. Fendrych, Matyáš ACORBA: Automated workflow to measure Arabidopsis thaliana root tip angle dynamics |
title | ACORBA: Automated workflow to measure Arabidopsis thaliana root tip angle dynamics |
title_full | ACORBA: Automated workflow to measure Arabidopsis thaliana root tip angle dynamics |
title_fullStr | ACORBA: Automated workflow to measure Arabidopsis thaliana root tip angle dynamics |
title_full_unstemmed | ACORBA: Automated workflow to measure Arabidopsis thaliana root tip angle dynamics |
title_short | ACORBA: Automated workflow to measure Arabidopsis thaliana root tip angle dynamics |
title_sort | acorba: automated workflow to measure arabidopsis thaliana root tip angle dynamics |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10095971/ https://www.ncbi.nlm.nih.gov/pubmed/37077987 http://dx.doi.org/10.1017/qpb.2022.4 |
work_keys_str_mv | AT serrenelsonbc acorbaautomatedworkflowtomeasurearabidopsisthalianaroottipangledynamics AT fendrychmatyas acorbaautomatedworkflowtomeasurearabidopsisthalianaroottipangledynamics |