Abstract
Accessing a plant's 3D geometry has become of significant importance for phenotyping during the last few years. Close-up laser scanning is an established method to acquire 3D plant shapes in real time with high detail, but it is stationary and has high investment costs. 3D reconstruction from images using structure from motion (SfM) and multi-view stereo (MVS) is a flexible cost-effective method, but requires post-processing procedures. The aim of this study is to evaluate the potential measuring accuracy of an SfM- and MVS-based photogrammetric method for the task of organ-level plant phenotyping. For this, reference data are provided by a high-accuracy close-up laser scanner. Using both methods, point clouds of several tomato plants were reconstructed at six following days. The parameters leaf area, main stem height and convex hull of the complete plant were extracted from the 3D point clouds and compared to the reference data regarding accuracy and correlation. These parameters were chosen regarding the demands of current phenotyping scenarios. The study shows that the photogrammetric approach is highly suitable for the presented monitoring scenario, yielding high correlations to the reference measurements. This cost-effective 3D reconstruction method depicts an alternative to an expensive laser scanner in the studied scenarios with potential for automated procedures.
Highlights
With the rise of phenotyping, the demand for access to the plants’ 3D shape has become of significant importance [1]
Close-up laser scanning has shown its advantage of high accuracy and high resolution [6] combined with direct access to the point cloud, but requires huge investment costs (100 kC) in advance
All parameters extracted from the Pix4DMapper point clouds yielded high correlations of R2 ≥ 0.96 to the parameters from the reference point clouds
Summary
With the rise of phenotyping, the demand for access to the plants’ 3D shape has become of significant importance [1]. Various methods using laser scanning [2], time of flight cameras [3,4] or structured light approaches [5], opening the door to 3D phenotyping, have been published. Close-up laser scanning has shown its advantage of high accuracy and high resolution [6] combined with direct access to the point cloud, but requires huge investment costs (100 kC) in advance. Using the 3D shape, descriptive parameters, like the plant volume or the geometry of single organs, can be extracted. The effect of occlusion, a huge challenge in 2D phenotyping approaches [7,8], can be reduced tremendously
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