A practical introduction to skeletons for the plant sciences

Abstract

Before the availability of digital photography resulting from the invention of charged couple devices in 1969, the measurement of plant architecture was a manual process either on the plant itself or on traditional photographs. The introduction of cheap digital imaging devices for the consumer market enabled the wide use of digital images to capture the shape of plant networks such as roots, tree crowns, or leaf venation. Plant networks contain geometric traits that can establish links to genetic or physiological characteristics, support plant breeding efforts, drive evolutionary studies, or serve as input to plant growth simulations. Typically, traits are encoded in shape descriptors that are computed from imaging data. Skeletons are one class of shape descriptors that are used to describe the hierarchies and extent of branching and looping plant networks. While the mathematical understanding of skeletons is well developed, their application within the plant sciences remains challenging because the quality of the measurement depends partly on the interpretation of the skeleton. This article is meant to bridge the skeletonization literature in the plant sciences and related technical fields by discussing best practices for deriving diameters and approximating branching hierarchies in a plant network.

How to make sense of 3D representations for plant phenotyping: a compendium of processing and analysis techniques

“…These techniques make use of different theoretical frameworks such as topological thinning or medial axes. For a review of methods in the context of plant images, see Bucksch [53] and for a more general overview of methods, see Cornea et al [54]. Skeletonization usually results in a set of voxels or points that in a final step are connected into an undirected graph, and on which subsequent analyses can be performed.…”

Morphological plant modeling: Unleashing geometric and topological potential within the plant sciences

“…Laser scanning and the complementary approach of stereovision both produce surface samples or point clouds as output. However, both approaches face algorithmic challenges encountered when plant parts occlude each other, since both rely on the reflection of waves from the plant surface (Bucksch, 2014a). Radar provides another non-invasive technique to study individual tree and forest structures over wide areas.…”

“…Their representation is intuitive because they can easily be reduced to intersecting line segments. A plethora of approaches to reduce imaged branching structures in 2D and 3D to lines or skeletons exist (see Bucksch 2011 and Bucksch, 2014a for an overview). In principle, skeletons let us navigate through a branching structure and take measurements of branch length and diameter.…”

“…One intuitive representation of the plant form relies on the use of skeletal descriptors that reduce the branching morphology of plants to a set of intersecting lines or curve segments, constituting a mathematical graph. These skeleton-based mathematical graphs can be derived from manual measurement (Godin et al, 1999; Watanabe et al, 2005) or imaging data (Bucksch et al, 2010; Bucksch 2011; Bucksch, 2014a; Aiteanu and Klein, 2014). Such skeletal descriptions can be used to derive quantitative measurements of lengths, diameters, and angles in tree crowns (Bucksch and Fleck, 2011; Raumonen et al, 2013; Seidel et al, 2015) and roots, at a single time point (Fitter, 1987; Danjon et al, 1999; Lobet et al, 2011; Galkovskyi et al, 2012) or over time to capture growth dynamics (Symonova et al, 2015).…”

“…Each curve segment is denoted by an edge, and a vertex denotes a connection. Augmenting each vertex with a 3D coordinate results in a skeletal 3D representation of plant architecture derivable from imaging data (Bucksch et al, 2010; Bucksch, 2014a; Aiteanu and Klein, 2014). Such skeletal descriptions are used to derive quantitative measurements of lengths, diameters, and angles (Bucksch and Fleck, 2011; Raumonen et al, 2013; Seidel et al, 2015).…”