Abstract
ABSTRACTPremiseLeaf epidermal cell morphology is closely tied to plants’ evolutionary histories and growth environments, and is therefore of interest to many plant biologists. However, cell measurement can be time-consuming and restrictive with current methods. CuticleTrace is a suite of FIJI and R-based functions that streamlines and automates the segmentation and measurement of epidermal pavement cells across a wide range of cell morphologies and image qualities.Methods and ResultsWe evaluated CuticleTrace-generated measurements against those from alternate automated methods and expert and undergraduate hand-tracings across a taxonomically diverse 50-image dataset of variable image qualities. We observed ∼93% statistical agreement between CuticleTrace and expert hand-traced measurements, outperforming alternate methods.ConclusionsCuticleTrace is broadly applicable, modular, and customizable, and integrates data visualization and cell shape measurement with image segmentation, lowering the barrier to high-throughput studies of epidermal morphology by vastly decreasing the labor investment required to generate high-quality cell shape datasets.
Publisher
Cold Spring Harbor Laboratory