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

Wang, G.ORCID: 0000-0002-5258-0532, Laga, H.ORCID: 0000-0002-4758-7510, Jia, J., Miklavcic, S.J. and Srivastava, A. (2020) Statistical analysis and modeling of the geometry and topology of plant roots. Journal of Theoretical Biology, 486 . Article 110108.

Link to Published Version: https://doi.org/10.1016/j.jtbi.2019.110108
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Abstract

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.

Item Type: Journal Article
Murdoch Affiliation: Information Technology, Mathematics and Statistics
Publisher: Elsevier
Copyright: © 2019 Elsevier Ltd.
URI: http://researchrepository.murdoch.edu.au/id/eprint/54066
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