Autor: |
Marie Theiß, Angelina Steier, Uwe Rascher, Mark Müller-Linow |
Jazyk: |
angličtina |
Rok vydání: |
2024 |
Předmět: |
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Zdroj: |
Plant Methods, Vol 20, Iss 1, Pp 1-16 (2024) |
Druh dokumentu: |
article |
ISSN: |
1746-4811 |
DOI: |
10.1186/s13007-023-01130-x |
Popis: |
Abstract Background The leaf angle distribution (LAD) is an important structural parameter of agricultural crops that influences light interception, radiation fluxes and consequently plant performance. Therefore, LAD and its parametrized form, the Beta distribution, is used in many photosynthesis models. However, in field cultivations, these parameters are difficult to assess and cereal crops in particular pose challenges since their leaves are thin, flexible, and often bent and twisted around their own axis. To our knowledge, there is only a very limited set of methods currently available to calculate LADs of field-grown cereal crops that explicitly takes these special morphological properties into account. Results In this study, a new processing pipeline is introduced that allows for the generation of realistic leaf surface models and the analysis of LADs of field-grown cereal crops from 3D point clouds. The data acquisition is based on a convenient stereo imaging setup. The approach was validated with different artificial targets and results on the accuracy of the 3D reconstruction, leaf surface modeling and calculated LAD are given. The mean error of the 3D reconstruction was below 1 mm for an inclination angle range between 0° and 75° and the leaf surface could be quantified with an average accuracy of 90%. The concordance correlation coefficient (CCC) of 99.6% (p-value = $$1.5* {10}^{-29}$$ 1.5 ∗ 10 - 29 ) indicated a high correlation between the reconstructed inclination angle and the identity line. The LADs for bent leaves were reconstructed with a mean error of 0.21° and a standard deviation of 1.55°. As an additional parameter, the insertion angle was reconstructed for the artificial leaf model with an average error |
Databáze: |
Directory of Open Access Journals |
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