Plant Sciences & Plant Pathology

Permanent URI for this communityhttps://scholarworks.montana.edu/handle/1/12

The Department of Plant Sciences and Plant Pathology is part of the College of Agriculture at Montana State University in Bozeman. An exciting feature of this department is the diversity of programs in Plant Biology, Crop Science, Plant Pathology, Horticulture, Mycology, Plant Genetics and Entomology. The department offers BS, MS, and Ph.D. degree program

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    Canopeo app as image-based phenotyping tool in controlled environment utilizing Arabidopsis mutants
    (Public Library of Science, 2024-03) Hale, Gabriella; Yuan, Ning; Mendu, Lavanya; Ritchie, Glen; Mendu, Venugopal
    Canopeo 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.
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