Automatic reconstruction of three-dimensional root system architecture based on ground penetrating radar

Fan, Guoqiu; Liang, Hao; Zhao, Yandong; Li, Yinghang

doi:10.1016/j.compag.2022.106969

Cited by 11 publications

(3 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Plant roots have diverse and complex 3D formations, which determines plants' efficiency in acquiring water and nutrients in the soil (Morris et al, 2017). New technologies such as magnetic resonance imaging(MRI) and X-ray computer tomography (X-ray CT), ground penetrating radar (GPR) have been adopted to observe roots on 3D scale in the lab and the field (Rellan- Alvarez et al, 2015;Morris et al, 2017;Fan et al, 2022). 3D models have been developed to quantify RSA.…”

mentioning

confidence: 99%

Responses of root system architecture to water stress at multiple levels: A meta-analysis of trials under controlled conditions

2022

View full text Add to dashboard Cite

Plants are exposed to increasingly severe drought events and roots play vital roles in maintaining plant survival, growth, and reproduction. A large body of literature has investigated the adaptive responses of root traits in various plants to water stress and these studies have been reviewed in certain groups of plant species at a certain scale. Nevertheless, these responses have not been synthesized at multiple levels. This paper screened over 2000 literatures for studies of typical root traits including root growth angle, root depth, root length, root diameter, root dry weight, root-to-shoot ratio, root hair length and density and integrates their drought responses at genetic and morphological scales. The genes, quantitative trait loci (QTLs) and hormones that are involved in the regulation of drought response of the root traits were summarized. We then statistically analyzed the drought responses of root traits and discussed the underlying mechanisms. Moreover, we highlighted the drought response of 1-D and 2-D root length density (RLD) distribution in the soil profile. This paper will provide a framework for an integrated understanding of root adaptive responses to water deficit at multiple scales and such insights may provide a basis for selection and breeding of drought tolerant crop lines.

show abstract

mentioning

confidence: 99%

Responses of root system architecture to water stress at multiple levels: A meta-analysis of trials under controlled conditions

2022

View full text Add to dashboard Cite

show abstract

“…The morphology of tree trunks inside real-world plots is approximately cylindrical, albeit with deviations from the ideal cylindrical shape [31,32]. The precise identification of tree trunks within plots that have intricate understory habitats, characterized by the presence of numerous non-tree disturbances resembling tree trunks, poses a significant obstacle.…”

Section: Important Parameters In the Individual Tree Segmentation Alg...mentioning

confidence: 99%

Improved Tree Segmentation Algorithm Based on Backpack-LiDAR Point Cloud

Zhu,

Liu,

Zheng

et al. 2024

Forests

View full text Add to dashboard Cite

For extracting tree structural data from LiDAR point clouds, individual tree segmentation is of great significance. Most individual tree segmentation algorithms miss segmentation and misrecognition, requiring manual post-processing. This study utilized a hierarchical approach known as segmentation based on hierarchical strategy (SHS) to improve individual tree segmentation. The tree point cloud was divided into the trunk layer and the canopy layer to carry out trunk detection and canopy segmentation, respectively. The effectiveness of SHS was evaluated on three mixed broadleaf forest plots. The segmentation efficacy of SHS was evaluated on three mixed broadleaf forest plots and compared with the point cloud segmentation algorithm (PCS) and the comparative shortest-path algorithm (CSP). In the three plots, SHS correctly identified all the trunk portion, had a recall (r) of 1, 0.98, and 1, a precision (p) of 1, and an overall segmentation rate (F) of 1, 0.99, and 1. CSP and PCS are less accurate than SHS. In terms of overall plots, SHS had 10%–15% higher F-scores than PCS and CSP. SHS extracted crown diameters with R2s of 0.91, 0.93, and 0.89 and RMSEs of 0.24 m, 0.23 m, and 0.30 m, outperforming CSP and PCS. Afterwards, we evaluate the three algorithms’ findings, examine the SHS algorithm’s parameters and constraints, and discuss the future directions of this research. This work offers an enhanced SHS that improves upon earlier research, addressing missed segmentation and misrecognition issues. It improves segmentation accuracy, individual tree segmentation, and provides both theoretical and data support for the LiDAR application in forest detection.

show abstract

“…This method was found to be effective in root biomass estimation. A root system architecture (RSA) was analysed by algorithms based on functions integrated with the root's biological properties, such as root point coordinate and diameter obtained by GPR, but these methods ignored the similarity of biological properties of adjacent tree roots, which sometimes results in the wrong estimation of the growing extension trend of root branches [150][151][152]. In [153],…”

Section: Tree Root Systems 3d Reconstructionmentioning

confidence: 99%

Advanced application of ground-penetrating radar in underground tree root systems detection and mapping

Luo

View full text Add to dashboard Cite

show abstract

Automatic reconstruction of three-dimensional root system architecture based on ground penetrating radar

Cited by 11 publications

References 31 publications

Responses of root system architecture to water stress at multiple levels: A meta-analysis of trials under controlled conditions

Responses of root system architecture to water stress at multiple levels: A meta-analysis of trials under controlled conditions

Improved Tree Segmentation Algorithm Based on Backpack-LiDAR Point Cloud

Advanced application of ground-penetrating radar in underground tree root systems detection and mapping

Contact Info

Product

Resources

About