LeafContourEFD: a reproducible workflow for elliptic Fourier analysis with orientation normalization and lateral asymmetry

Abstract

PremiseElliptic Fourier analysis is widely used to quantify leaf shape variation, but inconsistent normalization and orientation alignment can introduce biologically irrelevant variation. In addition, a reproducible workflow from raw images to normalized elliptic Fourier descriptors (EFDs) is still lacking. Methods and ResultsWe developed LeafContourEFD, a GUI application for reproducible leaf morphometrics. It integrates image segmentation, contour extraction, EFD calculation, and an extended normalization framework, termed oriented true EFD normalization, based on a user-defined biological reference axis. Analyses of Quercus serrata, Q. crispula, and Triadica sebifera showed that existing normalization methods can introduce orientation-related variance when the first-harmonic major axis does not match the leaf base-to-tip axis. In contrast, oriented true normalization removed these artifacts, yielding clearer shape transitions along principal components allowing shape variation among leaves to be captured while preserving biologically meaningful lateral asymmetry. ConclusionsLeafContourEFD improves interpretability and reproducibility in outline-based morphometrics and provides transparent outputs and metadata for data sharing and cross-study comparisons.