Using k-NN to analyse images of diverse germination phenotypes and detect single seed germination in Miscanthus sinensis

Abstract

With non-ideal seed images that included mould and broken seed the <i>k</i>-NN classifier was less consistent with human assessments. The most accurate assessment of germination with which to train classifiers is difficult to determine but the <i>k</i>-NN classifier provided an impartial consistent measurement of this important trait. It was more reproducible than the existing human scoring methods and was demonstrated to give a high degree of trueness to the human score.