Benjamin A. Lloyd, Richard S. Barclay, Regan E. Dunn, Ellen D. Currano, Ayuni I. Mohamaad, Kymbre Skersies, Surangi W. Punyasena
{"title":"CuticleTrace：捕捉叶片角质层细胞轮廓的工具包，对古生态学和古气候学具有重要意义","authors":"Benjamin A. Lloyd, Richard S. Barclay, Regan E. Dunn, Ellen D. Currano, Ayuni I. Mohamaad, Kymbre Skersies, Surangi W. Punyasena","doi":"10.1002/aps3.11566","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Premise</h3>\n \n <p>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.</p>\n </section>\n \n <section>\n \n <h3> Methods and Results</h3>\n \n <p>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.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>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.</p>\n </section>\n </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.11566","citationCount":"0","resultStr":"{\"title\":\"CuticleTrace: A toolkit for capturing cell outlines from leaf cuticle with implications for paleoecology and paleoclimatology\",\"authors\":\"Benjamin A. Lloyd, Richard S. Barclay, Regan E. Dunn, Ellen D. Currano, Ayuni I. Mohamaad, Kymbre Skersies, Surangi W. Punyasena\",\"doi\":\"10.1002/aps3.11566\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Premise</h3>\\n \\n <p>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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods and Results</h3>\\n \\n <p>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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusions</h3>\\n \\n <p>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.</p>\\n </section>\\n </div>\",\"PeriodicalId\":8022,\"journal\":{\"name\":\"Applications in Plant Sciences\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-02-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.11566\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applications in Plant Sciences\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/aps3.11566\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PLANT SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applications in Plant Sciences","FirstCategoryId":"99","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/aps3.11566","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PLANT SCIENCES","Score":null,"Total":0}
CuticleTrace: A toolkit for capturing cell outlines from leaf cuticle with implications for paleoecology and paleoclimatology
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.
期刊介绍：
Applications in Plant Sciences (APPS) is a monthly, peer-reviewed, open access journal promoting the rapid dissemination of newly developed, innovative tools and protocols in all areas of the plant sciences, including genetics, structure, function, development, evolution, systematics, and ecology. Given the rapid progress today in technology and its application in the plant sciences, the goal of APPS is to foster communication within the plant science community to advance scientific research. APPS is a publication of the Botanical Society of America, originating in 2009 as the American Journal of Botany''s online-only section, AJB Primer Notes & Protocols in the Plant Sciences.
APPS publishes the following types of articles: (1) Protocol Notes describe new methods and technological advancements; (2) Genomic Resources Articles characterize the development and demonstrate the usefulness of newly developed genomic resources, including transcriptomes; (3) Software Notes detail new software applications; (4) Application Articles illustrate the application of a new protocol, method, or software application within the context of a larger study; (5) Review Articles evaluate available techniques, methods, or protocols; (6) Primer Notes report novel genetic markers with evidence of wide applicability.
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