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Multiple Leaf Sample Extraction System (MuLES): A tool to improve automated morphometric leaf studies
PREMISE: The measurement of leaf morphometric parameters from digital images can be time‐consuming or restrictive when using digital image analysis softwares. The Multiple Leaf Sample Extraction System (MuLES) is a new tool that enables high‐throughput leaf shape analysis with minimal user input or...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10083438/ https://www.ncbi.nlm.nih.gov/pubmed/37051583 http://dx.doi.org/10.1002/aps3.11513 |
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author | Bowman, Christian S. Traband, Ryan Wang, Xuesong Knowles, Sara P. Lo, Sassoum Jia, Zhenyu Vorsa, Nicholi Herniter, Ira A. |
author_facet | Bowman, Christian S. Traband, Ryan Wang, Xuesong Knowles, Sara P. Lo, Sassoum Jia, Zhenyu Vorsa, Nicholi Herniter, Ira A. |
author_sort | Bowman, Christian S. |
collection | PubMed |
description | PREMISE: The measurement of leaf morphometric parameters from digital images can be time‐consuming or restrictive when using digital image analysis softwares. The Multiple Leaf Sample Extraction System (MuLES) is a new tool that enables high‐throughput leaf shape analysis with minimal user input or prerequisites, such as coding knowledge or image modification. METHODS AND RESULTS: MuLES uses contrasting pixel color values to distinguish between leaf objects and their background area, eliminating the need for color threshold–based methods or color correction cards typically required in other software methods. The leaf morphometric parameters measured by this software, especially leaf aspect ratio, were able to distinguish between large populations of different accessions for the same species in a high‐throughput manner. CONCLUSIONS: MuLES provides a simple method for the rapid measurement of leaf morphometric parameters in large plant populations from digital images and demonstrates the ability of leaf aspect ratio to distinguish between closely related plant types. |
format | Online Article Text |
id | pubmed-10083438 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100834382023-04-11 Multiple Leaf Sample Extraction System (MuLES): A tool to improve automated morphometric leaf studies Bowman, Christian S. Traband, Ryan Wang, Xuesong Knowles, Sara P. Lo, Sassoum Jia, Zhenyu Vorsa, Nicholi Herniter, Ira A. Appl Plant Sci Software Note PREMISE: The measurement of leaf morphometric parameters from digital images can be time‐consuming or restrictive when using digital image analysis softwares. The Multiple Leaf Sample Extraction System (MuLES) is a new tool that enables high‐throughput leaf shape analysis with minimal user input or prerequisites, such as coding knowledge or image modification. METHODS AND RESULTS: MuLES uses contrasting pixel color values to distinguish between leaf objects and their background area, eliminating the need for color threshold–based methods or color correction cards typically required in other software methods. The leaf morphometric parameters measured by this software, especially leaf aspect ratio, were able to distinguish between large populations of different accessions for the same species in a high‐throughput manner. CONCLUSIONS: MuLES provides a simple method for the rapid measurement of leaf morphometric parameters in large plant populations from digital images and demonstrates the ability of leaf aspect ratio to distinguish between closely related plant types. John Wiley and Sons Inc. 2023-03-21 /pmc/articles/PMC10083438/ /pubmed/37051583 http://dx.doi.org/10.1002/aps3.11513 Text en © 2023 The Authors. Applications in Plant Sciences is published by Wiley Periodicals LLC on behalf of Botanical Society of America. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Software Note Bowman, Christian S. Traband, Ryan Wang, Xuesong Knowles, Sara P. Lo, Sassoum Jia, Zhenyu Vorsa, Nicholi Herniter, Ira A. Multiple Leaf Sample Extraction System (MuLES): A tool to improve automated morphometric leaf studies |
title | Multiple Leaf Sample Extraction System (MuLES): A tool to improve automated morphometric leaf studies |
title_full | Multiple Leaf Sample Extraction System (MuLES): A tool to improve automated morphometric leaf studies |
title_fullStr | Multiple Leaf Sample Extraction System (MuLES): A tool to improve automated morphometric leaf studies |
title_full_unstemmed | Multiple Leaf Sample Extraction System (MuLES): A tool to improve automated morphometric leaf studies |
title_short | Multiple Leaf Sample Extraction System (MuLES): A tool to improve automated morphometric leaf studies |
title_sort | multiple leaf sample extraction system (mules): a tool to improve automated morphometric leaf studies |
topic | Software Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10083438/ https://www.ncbi.nlm.nih.gov/pubmed/37051583 http://dx.doi.org/10.1002/aps3.11513 |
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