A tool to model 3D coarse-root development with annual resolution

Abstract

Dynamic root-development models are indispensable for biomechanical and biomass allocation studies, and also play an important role in understanding slope stability. There are few rootdevelopment models in the literature, and there is a specific lack of dynamic models. Therefore, the aim of this study is to develop a 3D growth-development model for coarse roots, which is species independent, as long as annual rings are formed. In order to implement this model, the objectives are (I) to interpolate annual growth layers, and (II) to evaluate the interpolations and annual volume computations. The model developed is a combination of 3D laser scans and 2D tree-ring data. A FARO laser ScanArm is used to acquire the coarse-root structure. A MATLAB program then integrates the ringwidth measurements into the 3D model. A weighted interpolation algorithm is used to compute cross sections at any point within the model to obtain growth layers. The algorithm considers both the root structure and the ring-width data. The model reconstructed ring profiles with a mean absolute error for mean ring chronologies of <9% and for single radii of <20%. The interpolation accuracy was dependent on the number of input sections and root curvature. Total volume computations deviated by 3.5-6.6% from the reference model. A new robust root-modelling tool was developed which allows for annual volume computations and sophisticated root-development analyses.

Tree Root System Characterization and Volume Estimation by Terrestrial Laser Scanning and Quantitative Structure Modeling

“…GPR can describe large coarse root systems in situ under suitable conditions, but reliable accurate reconstructions of root systems in commonly encountered unsuitable conditions are still not possible [25]. Highly accurate (± 50 μm) laser scanning arms have been used to describe a whole root system (pine tree with an 8-cm DBH) down to a diameter of 0.5 mm, but scanning must be done by hand and post-processing times can be demanding with the methodology used by Wagner et al [37].…”

“…The use of TLS to describe 3D root systems is in its infancy, but has been identified as the best available technique to describe the architecture of large root systems, although it requires further development [8]. Early work has successfully represented the 3D structure of excavated individual root systems [33][34][35], calculated whole stump volume using slices [33,35] or by modeling the root surface [36,37], and investigated potential sources of error associated with various scanned materials, scanners, and point cloud post-processing techniques [35,38,39]. The volume of a root segment has been estimated from a triangulated root surface generated from a point cloud accurate to within ±50 μm as well as the feasibility of incorporating root growth ring data into the root reconstruction has also been investigated [36].…”

“…The volume of a root segment has been estimated from a triangulated root surface generated from a point cloud accurate to within ±50 μm as well as the feasibility of incorporating root growth ring data into the root reconstruction has also been investigated [36]. Building on this methodology, the volume of a whole complex root system and successive year growth surfaces and root volumes have been modeled [37]. Most recently, six Norway spruce stumps were mechanically pulled from the soil, scanned in the field, and the root architecture was recreated with a combination of a polyhedral grid for the stump and fit cylinders for the root portions of the root system [40], following the modeling methodology developed by Raumonen et al [30].…”

Detection of Disease Symptoms on Hyperspectral 3d Plant Models

“…By coupling with a measuring arm (Romer Infinite 2.0 in 2.8m version) it provides an occlusion-free option for close-up imaging of plants with a point reproducibility better than 0.1 mm. It is chosen due to its high resolution and accuracy and has been successfully applied for 3D imaging of various plants (Wagner et al, 2011;Paulus et al, 2013a).…”

Generation and application of hyperspectral 3D plant models: methods and challenges

“…Capturing the 3D geometry of plants is a common technique in plant science and can be applied across various scales ranging from laboratory [36] to greenhouse [18] and field [26]. A variety of sensor technologies, e.g., stereo camera system [8], terrestrial lidar [34], structured light approaches [6] or laser triangulation for close-up scanning [32] can be used to acquire the 3D geometry.…”