Abstract
Plant leaf movement is induced by some combination of different external and internal stimuli. Detailed geometric characterization of such movement is expected to improve understanding of these mechanisms. A metric high-quality, non-invasive and innovative sensor system to analyze plant movement is Terrestrial LiDAR (TLiDAR). This technique has an active sensor and is, therefore, independent of light conditions, able to obtain accurate high spatial and temporal resolution point clouds. In this study, a movement parameterization approach of leaf plants based on TLiDAR is introduced. For this purpose, two Calathea roseopicta plants were scanned in an indoor environment during 2 full-days, 1 day in natural light conditions and the other in darkness. The methodology to estimate leaf movement is based on segmenting individual leaves using an octree-based 3D-grid and monitoring the changes in their orientation by Principal Component Analysis. Additionally, canopy variations of the plant as a whole were characterized by a convex-hull approach. As a result, 9 leaves in plant 1 and 11 leaves in plant 2 were automatically detected with a global accuracy of 93.57 and 87.34%, respectively, compared to a manual detection. Regarding plant 1, in natural light conditions, the displacement average of the leaves between 7.00 a.m. and 12.30 p.m. was 3.67 cm as estimated using so-called deviation maps. The maximum displacement was 7.92 cm. In addition, the orientation changes of each leaf within a day were analyzed. The maximum variation in the vertical angle was 69.6° from 12.30 to 6.00 p.m. In darkness, the displacements were smaller and showed a different orientation pattern. The canopy volume of plant 1 changed more in the morning (4.42 dm3) than in the afternoon (2.57 dm3). The results of plant 2 largely confirmed the results of the first plant and were added to check the robustness of the methodology. The results show how to quantify leaf orientation variation and leaf movements along a day at mm accuracy in different light conditions. This confirms the feasibility of the proposed methodology to robustly analyse leaf movements.
Highlights
Plant canopy structure properties and their spatial changes, are linked to different vegetation processes, such as radiation absorption, plant water balance, precipitation interception and photosynthetic activity (Harley and Baldocchi, 1995)
The room temperature remained constant during the sampling period; the relative humidity changed between The first sampling day (test A) and B (Table 2)
The leaf movements of C. roseopicta plant 1 are illustrated in Figure 3, by superimposing the scan obtained at 7.00 a.m. to the one obtained at 12.30 p.m. during test A (Figure 3A) and by calculating the deviation map from the compared point cloud to the reference point cloud
Summary
Plant canopy structure properties and their spatial changes, are linked to different vegetation processes, such as radiation absorption, plant water balance, precipitation interception and photosynthetic activity (Harley and Baldocchi, 1995). In ecology and plant physiology, circadian rhythms are activities that occur on a near-24-h cycle due to ecologically useful adaptions, regarding plant’s physiology and its environment (Sadava et al, 2009). In this context, the growth patterns of roots and leaves are determined by the circadian clock and leaf starch metabolism (Ruts et al, 2012). Many successes are reported, image based techniques may require the use of a flash during low-light conditions, while some effort is needed in setup and/or processing to manually or automatically obtain 3D results
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