Quantitative Evaluation of Soybean (Glycine max L. Merr.) Leaflet Shape by Principal Component Scores Based on Elliptic Fourier Descriptor.

Abstract

Leaflet shape of thirty-nine soybean cultivars/strains selected to cover the possible diversity of leaf shape, was quantitatively evaluated by principal components scores based on the elliptic Fourier descriptor of contours. After central leaflets of fully expanded compound-leaves of the cultivars/strains were videotaped, binary images of the leaflets were obtained from those video images by image processing. Then, the closed contour of each leaflet was extracted from the binary images and chain-coded by image processing. Because the first twenty harmonics could sufficiently represent soybean leaf contours, 77 elliptic Fourier coefficients were calculated for each chain-coded contour. Then, the Fourier coefficients were standardized so that the coefficients were invariant of the size, rotation, shift and chain-code starting-point of any contour. The principal component analysis about the standardized Fourier coefficients, showed that the cumulative contribution at the fifth principal component was about 96 o/o' Moreover, the effect of each principal component on the leaf shape was clarified by drawing the contours of leaflets using the Fourier coefficients inversely estimated under some typical values of the principal component scores. Consequently, it was indicated that the principal components scores about the standardized elliptic Fourier coefficients gave us powerful quantitative measures to evaluate soybean leaf shape. The analysis of variance and multiple comparison indicated that the genotypic differences on the first, the second and the fifth principal components were significantly large. Because the variations of those principal components were con-tinuous, the effects of the polygenes on the (size-invariant) shape were also suggested.