title: A growth phenotyping pipeline for Arabidopsis thaliana integrating image analysis and rosette area modeling for robust quantification of genotype effects.
abstract: • To gain a deeper understanding of the mechanisms behind biomass accumulation, it is important to study plant growth behavior. Manually phenotyping large sets of plants requires important human resources and expertise and is typically not feasible for detection of weak growth phenotypes. Here, we established an automated growth phenotyping pipeline for Arabidopsis thaliana to aid researchers in comparing growth behaviors of different genotypes. • The analysis pipeline includes automated image analysis of two-dimensional digital plant images and evaluation of manually annotated information of growth stages. It employs linear mixed-effects models to quantify genotype effects on total rosette area and relative leaf growth rate (RLGR) and ANOVAs to quantify effects on developmental times. • Using the system, a single researcher can phenotype up to 7000 plants d⁻¹. Technical variance is very low (typically < 2%). We show quantitative results for the growth-impaired starch-excess mutant sex4-3 and the growth-enhanced mutant grf9. • We show that recordings of environmental and developmental variables reduce noise levels in the phenotyping datasets significantly and that careful examination of predictor variables (such as d after sowing or germination) is crucial to avoid exaggerations of recorded phenotypes and thus biased conclusions.
authors.affiliation: Institute of Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany.|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam, Germany.
authors.forename: Samuel
authors.initials: S
authors.lastname: Arvidsson
authors.affiliation: Colegio de Postgraduados, Km 36.5 Carretera México, Texcoco, Montecillo, Estado de México, C.P. 56230, México.
authors.forename: Paulino
authors.initials: P
authors.lastname: Pérez-Rodríguez
authors.affiliation: Institute of Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany.|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam, Germany.
authors.forename: Bernd
authors.initials: B
authors.lastname: Mueller-Roeber
mesh_terms: D017360:Arabidopsis / Q000145:classification / Q000235:genetics / Q000254:growth & development*; D029681:Arabidopsis Proteins / Q000235:genetics; D018533:Biomass; D054637:Dual-Specificity Phosphatases / Q000235:genetics; D005838:Genotype; D018525:Germination; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D016014:Linear Models; D008954:Models, Biological; D009154:Mutation; D010641:Phenotype; D018515:Plant Leaves / Q000254:growth & development; D036226:Seedlings / Q000254:growth & development; D012984:Software; D013213:Starch / Q000378:metabolism; D013997:Time Factors
chemical_list: D029681:Arabidopsis Proteins; D054637:Dual-Specificity Phosphatases; D013213:Starch; C553186:At3g52180 protein, Arabidopsis