rosettR: protocol and software for seedling area and growth analysis

Abstract

BackgroundGrowth is an important parameter to consider when studying the impact of treatments or mutations on plant physiology. Leaf area and growth rates can be estimated efficiently from images of plants, but the experiment setup, image analysis, and statistical evaluation can be laborious, often requiring substantial manual effort and programming skills.ResultsHere we present rosettR, a non-destructive and high-throughput phenotyping protocol for the measurement of total rosette area of seedlings grown in plates in sterile conditions. We demonstrate that our protocol can be used to accurately detect growth differences among different genotypes and in response to light regimes and osmotic stress. rosettR is implemented as a package for the statistical computing software R and provides easy to use functions to design an experiment, analyze the images, and generate reports on quality control as well as a final comparison across genotypes and applied treatments. Experiment procedures are included as part of the package documentation.ConclusionsUsing rosettR it is straight-forward to perform accurate, reproducible measurements of rosette area and relative growth rate with high-throughput using inexpensive equipment. Suitable applications include screening mutant populations for growth phenotypes visible at early growth stages and profiling different genotypes in a wide variety of treatments.

Crop Phenomics: Current Status and Perspectives

“…Corn leaf segment; graph to object converter; HSI TO GRAY converter, etc. Golzarian et al, 2011;Chen D. et al, 2014;Neilson et al, 2015;Amanda et al, 2016;Arend et al, 2016b;Cai et al, 2016;Guo et al, 2017;Liang et al, 2017;Majewsky et al, 2017;Meng et al, 2017;Neumann et al, 2017;Pandey et al, 2017;Parlati et al, 2017;Tomé et al, 2017; Crops within a 10-20 m × 110-200 m area can be monitored, which realizes the continuous, automatic, and high-throughput detection of crop phenotyping detection in field (Virlet et al, 2016;Sadeghi-Tehran et al, 2017). Meanwhile, the cablesuspended field phenotyping platform covering an area of ∼1 ha was also developed for rapid and non-destructive monitoring of crop traits (Kirchgessner et al, 2016).…”

Circadian control of abscisic acid biosynthesis and signalling pathways revealed by genome‐wide analysis of LHY binding targets

“…Plants were photographed at 7 and 10 d, then daily for the remaining 8 d of the experiment. Rosette area was then analysed using the ROSETTR software (Tome et al, 2017).…”

An Automated Method for High-Throughput Screening of Arabidopsis Rosette Growth in Multi-Well Plates and Its Validation in Stress Conditions

“…Thus, the maximum number of experimental variants per experiment, e.g., the number of simultaneously studied growth conditions, is determined by the number of plants per variant and the number of technical replicates of each variant. Recently, new methods using semi-automated systems of image acquisition by microscope or scanner for scoring Arabidopsis growth in vitro in 15 cm Petri dishes and 24-well plates, respectively, were published, allowing an increase in the number of plants per treatment and number of replicates ( Rodriguez-Furlán et al, 2016 ; Tomé et al, 2017 ).…”