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

Area of Science:

• Plant Biology
• Agricultural Technology
• Genetics

Background:

• Plant phenotyping is crucial for understanding plant growth and development.
• The Canopeo app offers a free, accessible tool for analyzing ground cover fraction (GCF) from RGB images.
• Evaluating Canopeo's utility in controlled environments for model plants is needed.

Purpose of the Study:

• To assess the effectiveness of the Canopeo app for plant phenotyping in a controlled environment.
• To compare growth differences in Arabidopsis thaliana mutants with altered FLAVIN-BINDING, KELCH REPEAT, F-BOX-1 (FKF1) gene expression.
• To determine if Canopeo can accurately estimate biomass and identify variations in resource allocation.

Main Methods:

• Utilized the Canopeo app to analyze ground cover fraction (GCF) from RGB images of Arabidopsis thaliana.
• Compared wild type (Col-0) with two FKF1 mutant lines: null expression (fkf1-t) and overexpression (FKF1-OE).
• Phenotyped plants under controlled long-day photoperiod conditions to estimate biomass and observe growth habits.

Main Results:

• The fkf1-t mutant exhibited increased biomass accumulation, enhanced cellulose biosynthesis, and delayed senescence under long-day conditions.
• The FKF1-OE line displayed a determinative growth habit, prioritizing resource allocation towards seed production.
• Canopeo successfully differentiated growth characteristics and biomass estimations among the Arabidopsis mutants.

Conclusions:

• Canopeo is a valuable and cost-efficient tool for plant phenotyping in controlled environments, even for researchers with limited resources.
• The study validates Canopeo's application for model organisms like Arabidopsis thaliana.
• Findings highlight the potential of Canopeo for phenotyping broadleaved crops in laboratory settings.