Abstract
Detailed 3D plant architectural data have numerous applications in plant science, but many existing approaches for 3D data collection are time-consuming and/or require costly equipment. Recently, there has been rapid growth in the availability of low-cost, 3D cameras and related open source software applications. 3D cameras may provide measurements of key components of plant architecture such as stem diameters and lengths, however, few tests of 3D cameras for the measurement of plant architecture have been conducted. Here, we measured Salix branch segments ranging from 2–13 mm in diameter with an Asus Xtion camera to quantify the limits and accuracy of branch diameter measurement with a 3D camera. By scanning at a variety of distances we also quantified the effect of scanning distance. In addition, we also test the sensitivity of the program KinFu for continuous 3D object scanning and modeling as well as other similar software to accurately record stem diameters and capture plant form (<3 m in height). Given its ability to accurately capture the diameter of branches >6 mm, Asus Xtion may provide a novel method for the collection of 3D data on the branching architecture of woody plants. Improvements in camera measurement accuracy and available software are likely to further improve the utility of 3D cameras for plant sciences in the future.
Highlights
Understanding the structure and characteristics of plant canopies is crucial for developing a more thorough understanding of many facets of plant ecology
We found that branches below 6.5 mm in diameter were not detected by the camera i.e., there was no point cloud data generated
For branches ~7 mm in diameter bias was +4 mm, and for branches greater than 7 mm in diameter measurement bias decreased to +2 mm
Summary
Understanding the structure and characteristics of plant canopies is crucial for developing a more thorough understanding of many facets of plant ecology. The inclusion of accurate descriptions of canopy architecture and development into plant modeling has led to the development of an important field of research in plant science—functional-structural plant modeling (FSPM) [5]. FSPM presently offers new insights in simulating-analyzing plant architecture in relation to genetic variability or in response to experimental manipulation and evaluating the implications of theses sources of variations on plant performance, crop production, pathogens invasion, and soil stability [5,6]. FSPM approaches are constraints by the quality of plant architectural measurements because 3D plant growth models calibrations require a wealth of architectural data in order to accurately simulate tree development and growth in silico [7,8,9]. To compute carbon assimilation using simulations of light interception by canopies, researchers require accurate data on branches and leaves and their orientation in 3D space [10]
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