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

  • Xiang Jiao
  • Huichun ZhangEmail author
  • Jiaqiang Zheng
  • Yue Yin
  • Guosu Wang
  • Ying Chen
  • Jun Yu
  • Yufeng Ge
Original Article


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).


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



The authors sincerely appreciate the National Natural Science Foundation of China (31371963), Natural Science Foundation of Jiangsu Province (BK20130965), Postgraduate research and Practice Innovation Program of Jiangsu Province (KYZZ16_0316) and Qing Lan Project of Jiangsu Province for supporting the research financially. The authors also express their gratitude to the editors and anonymous reviewers, whose comments and suggestions were extremely valuable for the improvement of the manuscript.


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Copyright information

© Franciszek Górski Institute of Plant Physiology, Polish Academy of Sciences, Kraków 2018

Authors and Affiliations

  1. 1.College of Mechanical and Electronic EngineeringNanjing Forestry UniversityNanjingChina
  2. 2.College of ForestryNanjing Forestry UniversityNanjingChina
  3. 3.Department of Mathematics and Mathematical StatisticsUmea UniversityUmeåSweden
  4. 4.Department of Biological Systems EngineeringUniversity of Nebraska-LincolnLincolnUSA

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