CuticleTrace: A toolkit for capturing cell outlines from leaf cuticle with implications for paleoecology and paleoclimatology

• Published in: Applications in plant sciences Vol. 12; no. 1; pp. e11566 - n/a
• Main Authors: Lloyd, Benjamin A., Barclay, Richard S., Dunn, Regan E., Currano, Ellen D., Mohamaad, Ayuni I., Skersies, Kymbre, Punyasena, Surangi W.
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01.01.2024; John Wiley and Sons Inc; Wiley
• Subjects: Automation; Batch processing; cell shape; Cell size; cell structures; Cells; Cytology; data collection; data visualization; Datasets; Fiji; high‐throughput phenotyping; image analysis; Image processing; image segmentation; labor; leaf area index; leaf epidermis; Leaves; Macros; Morphology; paleobotany; Paleoclimatology; Paleoecology; pavements; Plant cuticle; Software; Software Note; Taxonomy; Fiji; image processing; paleobotany; paleoecology; cell shape; image segmentation; leaf epidermis; leaf area index; high‐throughput phenotyping
• ISSN: 2168-0450; 2168-0450
• DOI: 10.1002/aps3.11566

Premise Leaf epidermal cell morphology is closely tied to the evolutionary history of plants and their 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 Results We evaluated CuticleTrace‐generated measurements against those from alternate automated methods and expert and undergraduate hand tracings across a taxonomically diverse 50‐image data set of variable image qualities. We observed ~93% statistical agreement between CuticleTrace and expert hand‐traced measurements, outperforming alternate methods. Conclusions CuticleTrace is a broadly applicable, modular, and customizable tool that 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 data sets.