How do roots interact with layered soils?
File(s)
Published version
Author(s)
Kemp, Nina
Angelidakis, Vasileios
Luli, Saimir
Nadimi, Sadegh
Type
Journal Article
Abstract
Vegetation alters soil fabric by providing biological reinforcement and enhancing the overall mechanical behaviour of slopes, thereby controlling shallow mass movement. To predict the behaviour of vegetated slopes, parameters representing the root system structure, such as root distribution, length, orientation and diameter, should be considered in slope stability models. This study quantifies the relationship between soil physical characteristics and root growth, giving special emphasis on (1) how roots influence the physical architecture of the surrounding soil structure and (2) how soil structure influences the root growth. A systematic experimental study is carried out using high-resolution X-ray micro-computed tomography (µCT) to observe the root behaviour in layered soil. In total, 2 samples are scanned over 15 days, enabling the acquisition of 10 sets of images. A machine learning algorithm for image segmentation is trained to act at 3 different training percentages, resulting in the processing of 30 sets of images, with the outcomes prompting a discussion on the size of the training data set. An automated in-house image processing algorithm is employed to quantify the void ratio and root volume ratio. This script enables post processing and image analysis of all 30 cases within few hours. This work investigates the effect of stratigraphy on root growth, along with the effect of image-segmentation parameters on soil constitutive properties.
Date Issued
2022-01-05
Date Acceptance
2021-12-16
Citation
Journal of Imaging, 2022, 8 (1)
ISSN
2313-433X
Publisher
MDPI AG
Start Page
5
End Page
5
Journal / Book Title
Journal of Imaging
Volume
8
Issue
1
Copyright Statement
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
License URL
Publication Status
Published
Article Number
ARTN 5
Date Publish Online
2022-01-05