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The leaf angle distribution of natural plant populations: assessing the canopy with a novel software tool.

Müller-Linow M, Pinto-Espinosa F, Scharr H, Rascher U - Plant Methods (2015)

Bottom Line: Based on the resulting surface meshes leaf angle statistics are computed on the whole-leaf level or from local derivations.In contrast nitrogen treatment had no effect on leaf angles.Our software package provides whole-leaf statistics but also a local estimation of leaf angles, which may have great potential to better understand and quantify structural canopy traits for guided breeding and optimized crop management.

View Article: PubMed Central - PubMed

Affiliation: Institute of Bio and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Wilhelm-Johnen-Str, Jülich, 52425 Germany.

ABSTRACT

Background: Three-dimensional canopies form complex architectures with temporally and spatially changing leaf orientations. Variations in canopy structure are linked to canopy function and they occur within the scope of genetic variability as well as a reaction to environmental factors like light, water and nutrient supply, and stress. An important key measure to characterize these structural properties is the leaf angle distribution, which in turn requires knowledge on the 3-dimensional single leaf surface. Despite a large number of 3-d sensors and methods only a few systems are applicable for fast and routine measurements in plants and natural canopies. A suitable approach is stereo imaging, which combines depth and color information that allows for easy segmentation of green leaf material and the extraction of plant traits, such as leaf angle distribution.

Results: We developed a software package, which provides tools for the quantification of leaf surface properties within natural canopies via 3-d reconstruction from stereo images. Our approach includes a semi-automatic selection process of single leaves and different modes of surface characterization via polygon smoothing or surface model fitting. Based on the resulting surface meshes leaf angle statistics are computed on the whole-leaf level or from local derivations. We include a case study to demonstrate the functionality of our software. 48 images of small sugar beet populations (4 varieties) have been analyzed on the base of their leaf angle distribution in order to investigate seasonal, genotypic and fertilization effects on leaf angle distributions. We could show that leaf angle distributions change during the course of the season with all varieties having a comparable development. Additionally, different varieties had different leaf angle orientation that could be separated in principle component analysis. In contrast nitrogen treatment had no effect on leaf angles.

Conclusions: We show that a stereo imaging setup together with the appropriate image processing tools is capable of retrieving the geometric leaf surface properties of plants and canopies. Our software package provides whole-leaf statistics but also a local estimation of leaf angles, which may have great potential to better understand and quantify structural canopy traits for guided breeding and optimized crop management.

No MeSH data available.


Stereo rig. Two cameras are fixed with a profile system and slightly turned to each other to capture the same scene. A remote-control release allows for synchronous triggering. In this setup the baseline was adjusted to b≈200 mm.
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Fig1: Stereo rig. Two cameras are fixed with a profile system and slightly turned to each other to capture the same scene. A remote-control release allows for synchronous triggering. In this setup the baseline was adjusted to b≈200 mm.

Mentions: Our software package has been developed to derive 3-d surface models and leaf surface parameters from stereo images of plants and plant canopies taken in a nadir perspective using ordinary cameras and lenses with a fixed focal length f. Such a setup is easy to handle and needs only a few additional components like a calibration pattern (for target calibration) and optionally an inclinometer and a compass to correct the direction and misalignment of the stereo rig. Figure 1 shows our example of the stereo rig. The two cameras need to be aligned in a fixed geometry (two clamps at the rigid metal profile in Figure 1). This setup is calibrated and must not be changed during image acquisition. This means also that all camera internal automation, especially auto-focus, need to be turned off. If applied on non-rigid objects like a moving canopy simultaneous exposure is of crucial importance and therefore cameras should be triggered via a remote-control release. To find the best depth resolution and depth of focus we provide a tool which helps to estimate the distances between cameras (which is the baseline b) and the distance between stereo rig and plants.Figure 1


The leaf angle distribution of natural plant populations: assessing the canopy with a novel software tool.

Müller-Linow M, Pinto-Espinosa F, Scharr H, Rascher U - Plant Methods (2015)

Stereo rig. Two cameras are fixed with a profile system and slightly turned to each other to capture the same scene. A remote-control release allows for synchronous triggering. In this setup the baseline was adjusted to b≈200 mm.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4359433&req=5

Fig1: Stereo rig. Two cameras are fixed with a profile system and slightly turned to each other to capture the same scene. A remote-control release allows for synchronous triggering. In this setup the baseline was adjusted to b≈200 mm.
Mentions: Our software package has been developed to derive 3-d surface models and leaf surface parameters from stereo images of plants and plant canopies taken in a nadir perspective using ordinary cameras and lenses with a fixed focal length f. Such a setup is easy to handle and needs only a few additional components like a calibration pattern (for target calibration) and optionally an inclinometer and a compass to correct the direction and misalignment of the stereo rig. Figure 1 shows our example of the stereo rig. The two cameras need to be aligned in a fixed geometry (two clamps at the rigid metal profile in Figure 1). This setup is calibrated and must not be changed during image acquisition. This means also that all camera internal automation, especially auto-focus, need to be turned off. If applied on non-rigid objects like a moving canopy simultaneous exposure is of crucial importance and therefore cameras should be triggered via a remote-control release. To find the best depth resolution and depth of focus we provide a tool which helps to estimate the distances between cameras (which is the baseline b) and the distance between stereo rig and plants.Figure 1

Bottom Line: Based on the resulting surface meshes leaf angle statistics are computed on the whole-leaf level or from local derivations.In contrast nitrogen treatment had no effect on leaf angles.Our software package provides whole-leaf statistics but also a local estimation of leaf angles, which may have great potential to better understand and quantify structural canopy traits for guided breeding and optimized crop management.

View Article: PubMed Central - PubMed

Affiliation: Institute of Bio and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Wilhelm-Johnen-Str, Jülich, 52425 Germany.

ABSTRACT

Background: Three-dimensional canopies form complex architectures with temporally and spatially changing leaf orientations. Variations in canopy structure are linked to canopy function and they occur within the scope of genetic variability as well as a reaction to environmental factors like light, water and nutrient supply, and stress. An important key measure to characterize these structural properties is the leaf angle distribution, which in turn requires knowledge on the 3-dimensional single leaf surface. Despite a large number of 3-d sensors and methods only a few systems are applicable for fast and routine measurements in plants and natural canopies. A suitable approach is stereo imaging, which combines depth and color information that allows for easy segmentation of green leaf material and the extraction of plant traits, such as leaf angle distribution.

Results: We developed a software package, which provides tools for the quantification of leaf surface properties within natural canopies via 3-d reconstruction from stereo images. Our approach includes a semi-automatic selection process of single leaves and different modes of surface characterization via polygon smoothing or surface model fitting. Based on the resulting surface meshes leaf angle statistics are computed on the whole-leaf level or from local derivations. We include a case study to demonstrate the functionality of our software. 48 images of small sugar beet populations (4 varieties) have been analyzed on the base of their leaf angle distribution in order to investigate seasonal, genotypic and fertilization effects on leaf angle distributions. We could show that leaf angle distributions change during the course of the season with all varieties having a comparable development. Additionally, different varieties had different leaf angle orientation that could be separated in principle component analysis. In contrast nitrogen treatment had no effect on leaf angles.

Conclusions: We show that a stereo imaging setup together with the appropriate image processing tools is capable of retrieving the geometric leaf surface properties of plants and canopies. Our software package provides whole-leaf statistics but also a local estimation of leaf angles, which may have great potential to better understand and quantify structural canopy traits for guided breeding and optimized crop management.

No MeSH data available.