Canopeo app as image-based phenotyping tool in controlled environment utilizing Arabidopsis mutants

dc.contributor.authorHale, Gabriella
dc.contributor.authorYuan, Ning
dc.contributor.authorMendu, Lavanya
dc.contributor.authorRitchie, Glen
dc.contributor.authorMendu, Venugopal
dc.date.accessioned2024-06-12T22:12:59Z
dc.date.available2024-06-12T22:12:59Z
dc.date.issued2024-03
dc.description.abstractCanopeo app was developed as a simple, accurate, rapid, and free tool to analyze ground cover fraction (GCF) from red-green-blue (RGB) images and videos captured in the field. With increasing interest in tools for plant phenotyping in controlled environments, the usefulness of Canopeo to identify differences in growth among Arabidopsis thaliana mutants in a controlled environment were explored. A simple imaging system was used to compare Arabidopsis mutants based on the FLAVIN-BINDING, KELCH REPEAT, F-BOX-1 (FKF1) mutation, which has been identified with increased biomass accumulation. Two FKF1 lines such as null expression (fkf1-t) and overexpression (FKF1-OE) lines were used along with wild type (Col-0). Canopeo was used to phenotype plants, based on biomass estimations. Under long-day photoperiod, fkf1-t had increased cellulose biosynthesis, and therefore biomass. Resource partitioning favored seedling vigor and delayed onset of senescence. In contrast, FKF1-OE illustrated a determinative growth habit where plant resources are primarily allocated for seed production. This study demonstrates the use of Canopeo for model plants and highlights its potential for phenotyping broadleaved crops in controlled environments. The value of adapting Canopeo for lab use is those with limited experience and resources have access to phenotyping methodology that is simple, accessible, accurate, and cost-efficient in a controlled environment setting.
dc.identifier.citationHale G, Yuan N, Mendu L, Ritchie G, Mendu V (2024) Canopeo app as image-based phenotyping tool in controlled environment utilizing Arabidopsis mutants. PLoS ONE 19(3): e0300667. https://doi.org/10.1371/journal.pone.0300667
dc.identifier.doi10.1371/journal.pone.0300667
dc.identifier.issn1932-6203
dc.identifier.urihttps://scholarworks.montana.edu/handle/1/18627
dc.language.isoen_US
dc.publisherPublic Library of Science
dc.rightscc-by
dc.subjectCanopeo app
dc.subjectimage based phenotyping
dc.subjectArabidopsis mutants
dc.titleCanopeo app as image-based phenotyping tool in controlled environment utilizing Arabidopsis mutants
dc.typeArticle
mus.citation.extentfirstpage1
mus.citation.extentlastpage23
mus.citation.journaltitlePLOS ONE
mus.data.thumbpage5
mus.relation.collegeCollege of Agriculture
mus.relation.departmentPlant Sciences & Plant Pathology
mus.relation.universityMontana State University - Bozeman

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
hale-canopeo-app-2024.pdf
Size:
3.13 MB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
825 B
Format:
Item-specific license agreed upon to submission
Description:
Copyright (c) 2002-2022, LYRASIS. All rights reserved.