SB and SWP supervised and 291 directed the research. 292 DATA AVAILABILITY 293 All generated and analyzed data from this study are included in the published article and its 294 Supporting Information (Fig. S2). The code for the FIJI macros as well as the R notebook for 295 filtering cells is available in the GitHub repository: (https://github.com/benjlloyd/CuticleTrace).296 REFERENCES 297 Aono, A. H., J. S. Nagai, G. da S. M. Dickel, R. C. Marinho, P. E. A. M. de Oliveira, J. P. Papa, 298 and F. A. Faria. 2021. A stomata classification and detection system in microscope 299 images of maize cultivars. PLOS ONE 16: e0258679. 300 Barclay, R., J. Mcelwain, D. Dilcher, and B. Sageman. 2007. The C
Open resource ↗benjlloyd/CuticleTrace · pdf-raw-page:13 lines:1-61Unverified paper record
CuticleTrace: A toolkit for capturing cell outlines of leaf cuticle with implications for paleoecology and paleoclimatology
bioRxiv · 22 Aug 2023 · 10.1101/2023.07.23.550217
Abstract
PremiseLeaf 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.
Plant phenotyping relevance
葉の表皮細胞形態を画像からセグメンテーション・測定するソフトウェアを開発し、代替手法および専門家の手トレースと比較検証しており、植物表現型取得法が研究の中心です。
abstractCuticleTrace 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.
abstractWe 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.
Code and data availability
The authors publicly release the CuticleTrace FIJI macros and R filtering notebook used for the paper's epidermal cell phenotyping analysis on GitHub, with explicit availability language and URL.
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