Ground-penetrating radar-based automatic reconstruction of three-dimensional coarse root system architecture

Root system architecture (RSA) refers to the geometric features and topology of the root system. Ground-penetrating radar (GPR) is a possible method of RSA reconstruction. However, because the topology of the root system is not directly accessible by GPR, GPR-based reconstruction must be complemented by manual connection of root points, resulting in limited accuracy. In this study, we used both GPR and direct excavation to obtain 3D coordinates (XYZ coordinates) and diameters of moso bamboo rhizomes on an orthogonal grid. A score function for selecting the best-connected root points was developed using rhizome diameter, depth, extension angle, and measured line spacing, which was then used to recover the topology of discrete root points. Based on the recovered topology, the 3D RSA of the rhizomes was reconstructed using a smoothing function. Based on the excavation data, the reconstructed RSA was generally consistent with the measured RSA, with 78.13% of root points correctly connected. The reconstructed RSA based on GPR data thus provided a rough approximation of the measured RSA, with errors arising due to missing root points and rhizome displacement. The proposed algorithm for reconstructing 3D RSA further enriches the application of ground-penetrating radar to root detection.

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Response of Mungbean Root System Architecture to Phosphorus Application Methods

Proceedings ◽

10.3390/proceedings2019036173 ◽

2020 ◽

Vol 36 (1) ◽

pp. 173

Author(s):

Vijaya Singh ◽

Marisa Collins ◽

Colin Andrew Douglas ◽

Michael Bell

Keyword(s):

Root System ◽

System Architecture ◽

Root Systems ◽

Root System Architecture ◽

Grain Legumes ◽

Coarse Root ◽

Root Parameters ◽

P Application ◽

Application Methods ◽

Phosphorus Application

In recent years phosphorus application methods have become an important management strategy for optimising the uptake of the immobile nutrient phosphorus (P). Root system architecture (RSA) could play a particularly important role in the uptake of P by grain legumes, due to their relatively coarse root systems. The objective of this study was to understand the response of mungbean root systems to P application methods. Four mungbean varieties were grown in purpose-built soil filled root chambers that received five P application methods. Phosphorus treatments consisted of a control (no application of P) compared with 30 mg P/kg soil throughout the soil volume (high P treatment) or restricted to 10cm deep layers in the topsoil or in a layer from 20-30cm deep. A fifth treatment consisted of the same amount of P as applied in deeper dispersed layer applied in a concentrated band at 25cm depth. After 50 days of growth, plant were destructively harvested and shoot and root parameters were measured. Mungbean varieties responded differently to P application methods, with Jade and Berken varieties showing greater root proliferation at depth and greater shoot growth in response to banded and deeper dispersed P applications, relative to the late maturing variety Putland. Shallow dispersed P and the no-P control both resulted in poor root growth in all the genotypes except Celera II, which did not respond to P application from any placement strategy. Results suggest that P application strategies may need to vary with variety to maximize the uptake of P.

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RSAtrace3D: robust vectorization software for measuring monocot root system architecture

BMC Plant Biology ◽

10.1186/s12870-021-03161-9 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Shota Teramoto ◽

Takanari Tanabata ◽

Yusaku Uga

Keyword(s):

Root System ◽

System Architecture ◽

Three Dimensional ◽

Root System Architecture ◽

Ct Images ◽

X Ray ◽

Single Root ◽

Base Points ◽

Using Data ◽

Crown Roots

Abstract Background The root distribution in the soil is one of the elements that comprise the root system architecture (RSA). In monocots, RSA comprises radicle and crown roots, each of which can be basically represented by a single curve with lateral root branches or approximated using a polyline. Moreover, RSA vectorization (polyline conversion) is useful for RSA phenotyping. However, a robust software that can enable RSA vectorization while using noisy three-dimensional (3D) volumes is unavailable. Results We developed RSAtrace3D, which is a robust 3D RSA vectorization software for monocot RSA phenotyping. It manages the single root (radicle or crown root) as a polyline (a vector), and the set of the polylines represents the entire RSA. RSAtrace3D vectorizes root segments between the two ends of a single root. By utilizing several base points on the root, RSAtrace3D suits noisy images if it is difficult to vectorize it using only two end nodes of the root. Additionally, by employing a simple tracking algorithm that uses the center of gravity (COG) of the root voxels to determine the tracking direction, RSAtrace3D efficiently vectorizes the roots. Thus, RSAtrace3D represents the single root shape more precisely than straight lines or spline curves. As a case study, rice (Oryza sativa) RSA was vectorized from X-ray computed tomography (CT) images, and RSA traits were calculated. In addition, varietal differences in RSA traits were observed. The vector data were 32,000 times more compact than raw X-ray CT images. Therefore, this makes it easier to share data and perform re-analyses. For example, using data from previously conducted studies. For monocot plants, the vectorization and phenotyping algorithm are extendable and suitable for numerous applications. Conclusions RSAtrace3D is an RSA vectorization software for 3D RSA phenotyping for monocots. Owing to the high expandability of the RSA vectorization and phenotyping algorithm, RSAtrace3D can be applied not only to rice in X-ray CT images but also to other monocots in various 3D images. Since this software is written in Python language, it can be easily modified and will be extensively applied by researchers in this field.

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