In a morphometric variability study of montane shrub species populations, which I have just launched, leaf shape would be quite a promising character. Although commonly used in such studies, leaf shape is often analysed as actually a set of individual “shape-describing” linear traits and their ratios, leaf area and perimeter. But still, each of these traits is treated by the analysis as an individual independent variable. Thus, I am looking for a high-precision method to measure and analyse leaf shape as a single whole.
The supposed algorithm is following: on the photographed or scanned leaf images, a number of control points are placed along the leaf outline in a computer program. The program then analyses the differences between leaf outlines based on these points, resulting in numerical/graphical representation of the leaf shape variation.
Having reviewed some literature, I found that this can be done by so-called Elliptic Fourier leaf shape analysis using R statistics. Has anyone dealt with such kind of analysis? Is it applicable for within-species population studies? This analysis can be carried out by any of numerous algorithms, so did anybody compare their effectiveness? Also, are there any easier-to-use substitutes for this method? I would be grateful for recommending a relevant statistics and software, some manuals and publications.
I have attached an article below, I hope it will be useful for you.
Best regards,
Vadim Polonskiy
Fourier shape analysis is quite common in fisheries studies where fish can be classified into groups by the shape of the otolith (ear bone). Momocs is a really neat package in R for this and the user guide should give you some good ideas on how to start.
regards,
james
Article Otolith shape analysis of blue whiting suggests a complex st...
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