Comparative analysis of nonlinear growth curve models for Arabidopsis thaliana rosette leaves

Xiang Jiao, Huichun Zhang, Jiaqiang Zheng, Yue Yin, Guosu Wang, Ying Chen, Jun Yu, Yufeng Ge

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


As a model organism, modeling and analysis of the phenotype of Arabidopsis thaliana (A. thaliana) leaves for a given genotype can help us better understand leaf growth regulation. A. thaliana leaves growth trajectories are to be nonlinear and the leaves contribute most to the above-ground biomass. Therefore, analysis of their change regulation and development of nonlinear growth models can better understand the phenotypic characteristics of leaves (e.g., leaf size) at different growth stages. In this study, every individual leaf size of A. thaliana rosette leaves was measured during their whole life cycle using non-destructive imaging measurement. And three growth models (Gompertz model, logistic model and Von Bertalanffy model) were analyzed to quantify the rosette leaves growth process of A. thaliana. Both graphical (plots of standardized residuals) and numerical measures (AIC, R2 and RMSE) were used to evaluate the fitted models. The results showed that the logistic model fitted better in describing the growth of A. thaliana leaves compared to Gompertz model and Von Bertalanffy model, as it gave higher R2 and lower AIC and RMSE for the leaves of A. thaliana at different growth stages (i.e., early leaf, mid-term leaf and late leaf).

Original languageEnglish (US)
Article number114
JournalActa Physiologiae Plantarum
Issue number6
StatePublished - Jun 1 2018


  • A. thaliana
  • Akaike’s information criterion
  • Growth model
  • Leaf area
  • Non-destructive imaging measurement

ASJC Scopus subject areas

  • Physiology
  • Agronomy and Crop Science
  • Plant Science


Dive into the research topics of 'Comparative analysis of nonlinear growth curve models for Arabidopsis thaliana rosette leaves'. Together they form a unique fingerprint.

Cite this