TY - JOUR
T1 - Comparative analysis of nonlinear growth curve models for Arabidopsis thaliana rosette leaves
AU - Jiao, Xiang
AU - Zhang, Huichun
AU - Zheng, Jiaqiang
AU - Yin, Yue
AU - Wang, Guosu
AU - Chen, Ying
AU - Yu, Jun
AU - Ge, Yufeng
N1 - Funding Information:
Acknowledgements 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.
Publisher Copyright:
© 2018, Franciszek Górski Institute of Plant Physiology, Polish Academy of Sciences, Kraków.
PY - 2018/6/1
Y1 - 2018/6/1
N2 - 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).
AB - 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).
KW - A. thaliana
KW - Akaike’s information criterion
KW - Growth model
KW - Leaf area
KW - Non-destructive imaging measurement
UR - http://www.scopus.com/inward/record.url?scp=85047359291&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85047359291&partnerID=8YFLogxK
U2 - 10.1007/s11738-018-2686-8
DO - 10.1007/s11738-018-2686-8
M3 - Article
AN - SCOPUS:85047359291
SN - 0137-5881
VL - 40
JO - Acta Physiologiae Plantarum
JF - Acta Physiologiae Plantarum
IS - 6
M1 - 114
ER -