Limits...
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.


GUI for surface modeling. Graphical user interface for surface modeling: Disparity data (left) and segmentation data (right) are combined in module 3 to approximate surfaces to 3-d point clouds according to different modeling options. Surfaces are either fitted according to planar, quadratic or cubic functions or smoothed using curvature flow or Laplace smoothing.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Fig7: GUI for surface modeling. Graphical user interface for surface modeling: Disparity data (left) and segmentation data (right) are combined in module 3 to approximate surfaces to 3-d point clouds according to different modeling options. Surfaces are either fitted according to planar, quadratic or cubic functions or smoothed using curvature flow or Laplace smoothing.

Mentions: Surface smoothing: For pre-processing we included a filter, which removes disjoined point clusters up to a particular size and distance to the major clusters. The resulting point clouds are firstly meshed via 2-d Delaunay triangulation on the base of x and y-coordinates to ensure the formation of only such faces reflecting the leaf surface. Faces with edge lengths or areas above predefined thresholds are removed in order to prevent cross-linking in non-plant sections (Figure 7 left - mesh parameters). The final 3-d triangulation, which is performed via unstructured triangular surface meshing, follows on the identification of the leaf border and holes. Holes within each segment, which appear due to fragmentary disparity maps and missing segmentation information, are identified and automatically removed, if they are below a predefined size. Resulting segment meshes are then individually smoothed with the curvature flow or the Laplace method depending on the user’s choice. Curvature flow requires 3 parameters, which are preset by the user and which regulate smoothing iteration, smoothing strength and neighborhood impact (Figure 7 left - point cloud).Figure 7


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)

GUI for surface modeling. Graphical user interface for surface modeling: Disparity data (left) and segmentation data (right) are combined in module 3 to approximate surfaces to 3-d point clouds according to different modeling options. Surfaces are either fitted according to planar, quadratic or cubic functions or smoothed using curvature flow or Laplace smoothing.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Fig7: GUI for surface modeling. Graphical user interface for surface modeling: Disparity data (left) and segmentation data (right) are combined in module 3 to approximate surfaces to 3-d point clouds according to different modeling options. Surfaces are either fitted according to planar, quadratic or cubic functions or smoothed using curvature flow or Laplace smoothing.
Mentions: Surface smoothing: For pre-processing we included a filter, which removes disjoined point clusters up to a particular size and distance to the major clusters. The resulting point clouds are firstly meshed via 2-d Delaunay triangulation on the base of x and y-coordinates to ensure the formation of only such faces reflecting the leaf surface. Faces with edge lengths or areas above predefined thresholds are removed in order to prevent cross-linking in non-plant sections (Figure 7 left - mesh parameters). The final 3-d triangulation, which is performed via unstructured triangular surface meshing, follows on the identification of the leaf border and holes. Holes within each segment, which appear due to fragmentary disparity maps and missing segmentation information, are identified and automatically removed, if they are below a predefined size. Resulting segment meshes are then individually smoothed with the curvature flow or the Laplace method depending on the user’s choice. Curvature flow requires 3 parameters, which are preset by the user and which regulate smoothing iteration, smoothing strength and neighborhood impact (Figure 7 left - point cloud).Figure 7

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.