TY  - JOUR
A1  - Arvidsson, Samuel Janne
A1  - Perez-Rodriguez, Paulino
A1  - Müller-Röber, Bernd
T1  - A growth phenotyping pipeline for Arabidopsis thaliana integrating image analysis and rosette area modeling for robust quantification of genotype effects
JF  - New phytologist : international journal of plant science
N2  - 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-excessmutant sex4-3 and the growth-enhancedmutant 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.
KW  - development
KW  - growth
KW  - leaf area
KW  - modeling
KW  - phenotyping
Y1  - 2011
U6  - https://doi.org/10.1111/j.1469-8137.2011.03756.x
SN  - 0028-646X
VL  - 191
IS  - 3
SP  - 895
EP  - 907
PB  - Wiley-Blackwell
CY  - Malden
ER  -