Anatomical features of Fagaceae wood statistically extracted by computer vision approaches: Some relationships with evolution.

Abstract

The anatomical structure of wood is complex and contains considerable information about its specific species, physical properties, growth environment, and other factors. While conventional wood anatomy has been established by systematizing the xylem anatomical features, which enables wood identification generally up to genus level, it is difficult to describe all the information comprehensively. This study apply two computer vision approaches to optical micrographs: the scale-invariant feature transform algorithm and connected-component labelling. They extract the shape and pore size information, respectively, statistically from the whole micrographs. Both approaches enable the efficient detection of specific features of 18 species from the family Fagaceae. Although the methods ignore the positional information, which is important for the conventional wood anatomy, the simple information on the shape or size of the elements is enough to describe the species-specificity of wood. In addition, according to the dendrograms calculated from the numerical distances of the features, the closeness of some taxonomic groups is inconsistent with the types of porosity, which is one of the typical classification systems for wood anatomy, but consistent with the evolution based on molecular phylogeny; for example, ring-porous group Cerris and radial-porous group Ilex are nested in the same cluster. We analyse which part of the wood structure gave the taxon-specific information, indicating that the latewood zone of group Cerris is similar to the whole zone of group Ilex. Computer vision approaches provide statistical information that uncovers new aspects of wood anatomy that have been overlooked by conventional visual inspection.