Statistical analysis and modeling of the geometry and topology of plant roots

JOURNAL OF THEORETICAL BIOLOGY

卷:486

Article

Wang, Guan¹  Laga, Hamid^2,3  Jia, Jinyuan¹  Miklavcic, Stanley J.³  Srivastava, Anuj⁴ 

[1] Tongji Univ, Sch Software Engn, Shanghai, Peoples R China

[2] Murdoch Univ, Informat Technol Math & Stat Discipline, Murdoch, WA, Australia

[3] Univ South Australia, Phenorn & Bioinformat Res Ctr, Adelaide, SA, Australia

[4] Florida State Univ, Dept Stat, Tallahassee, FL 32306 USA

关键词: Geodesics;    Tree-shape space;    Root shape alignment;    Shape analysis;    Principal component analysis;    Shape modeling;    Root shape synthesis;   

DOI  :  10.1016/j.jtbi.2019.110108

来源: Elsevier

【 摘 要 】

The root is an important organ of a plant since it is responsible for water and nutrient uptake. Analyzing and modeling variabilities in the geometry and topology of roots can help in assessing the plant's health, understanding its growth patterns, and modeling relations between plant species and between plants and their environment. In this article, we develop a framework for the statistical analysis and modeling of the geometry and topology of plant roots. We represent root structures as points in a tree-shape space equipped with a metric that quantifies geometric and topological differences between pairs of roots. We then use these building blocks to compute geodesics, i.e., optimal deformations under the metric between root structures, and to perform statistical analysis on root populations. We demonstrate the utility of the proposed framework through an application to a dataset of wheat roots grown in different environmental conditions. We also show that the framework can be used in various applications including classification and regression. (C) 2019 Elsevier Ltd. All rights reserved.

【 授权许可】

Free