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An automatic fluorescence phenotyping platform to evaluate dynamic infection process of Tobacco mosaic virus-green fluorescent protein in tobacco leaves
Tobacco is one of the important economic crops all over the world. Tobacco mosaic virus (TMV) seriously affects the yield and quality of tobacco leaves. The expression of TMV in tobacco leaves can be analyzed by detecting green fluorescence-related traits after inoculation with the infectious clone...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9478445/ https://www.ncbi.nlm.nih.gov/pubmed/36119566 http://dx.doi.org/10.3389/fpls.2022.968855 |
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author | Ye, Junli Song, Jingyan Gao, Yuan Lu, Xu Pei, Wenyue Li, Feng Feng, Hui Yang, Wanneng |
author_facet | Ye, Junli Song, Jingyan Gao, Yuan Lu, Xu Pei, Wenyue Li, Feng Feng, Hui Yang, Wanneng |
author_sort | Ye, Junli |
collection | PubMed |
description | Tobacco is one of the important economic crops all over the world. Tobacco mosaic virus (TMV) seriously affects the yield and quality of tobacco leaves. The expression of TMV in tobacco leaves can be analyzed by detecting green fluorescence-related traits after inoculation with the infectious clone of TMV-GFP (Tobacco mosaic virus - green fluorescent protein). However, traditional methods for detecting TMV-GFP are time-consuming and laborious, and mostly require a lot of manual procedures. In this study, we develop a low-cost machine-vision-based phenotyping platform for the automatic evaluation of fluorescence-related traits in tobacco leaf based on digital camera and image processing. A dynamic monitoring experiment lasting 7 days was conducted to evaluate the efficiency of this platform using Nicotiana tabacum L. with a total of 14 samples, including the wild-type strain SR1 and 4 mutant lines generated by RNA interference technology. As a result, we found that green fluorescence area and brightness generally showed an increasing trend over time, and the trends were different among these SR1 and 4 mutant lines samples, where the maximum and minimum of green fluorescence area and brightness were mutant-4 and mutant-1 respectively. In conclusion, the platform can full-automatically extract fluorescence-related traits with the advantage of low-cost and high accuracy, which could be used in detecting dynamic changes of TMV-GFP in tobacco leaves. |
format | Online Article Text |
id | pubmed-9478445 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94784452022-09-17 An automatic fluorescence phenotyping platform to evaluate dynamic infection process of Tobacco mosaic virus-green fluorescent protein in tobacco leaves Ye, Junli Song, Jingyan Gao, Yuan Lu, Xu Pei, Wenyue Li, Feng Feng, Hui Yang, Wanneng Front Plant Sci Plant Science Tobacco is one of the important economic crops all over the world. Tobacco mosaic virus (TMV) seriously affects the yield and quality of tobacco leaves. The expression of TMV in tobacco leaves can be analyzed by detecting green fluorescence-related traits after inoculation with the infectious clone of TMV-GFP (Tobacco mosaic virus - green fluorescent protein). However, traditional methods for detecting TMV-GFP are time-consuming and laborious, and mostly require a lot of manual procedures. In this study, we develop a low-cost machine-vision-based phenotyping platform for the automatic evaluation of fluorescence-related traits in tobacco leaf based on digital camera and image processing. A dynamic monitoring experiment lasting 7 days was conducted to evaluate the efficiency of this platform using Nicotiana tabacum L. with a total of 14 samples, including the wild-type strain SR1 and 4 mutant lines generated by RNA interference technology. As a result, we found that green fluorescence area and brightness generally showed an increasing trend over time, and the trends were different among these SR1 and 4 mutant lines samples, where the maximum and minimum of green fluorescence area and brightness were mutant-4 and mutant-1 respectively. In conclusion, the platform can full-automatically extract fluorescence-related traits with the advantage of low-cost and high accuracy, which could be used in detecting dynamic changes of TMV-GFP in tobacco leaves. Frontiers Media S.A. 2022-09-02 /pmc/articles/PMC9478445/ /pubmed/36119566 http://dx.doi.org/10.3389/fpls.2022.968855 Text en Copyright © 2022 Ye, Song, Gao, Lu, Pei, Li, Feng and Yang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Ye, Junli Song, Jingyan Gao, Yuan Lu, Xu Pei, Wenyue Li, Feng Feng, Hui Yang, Wanneng An automatic fluorescence phenotyping platform to evaluate dynamic infection process of Tobacco mosaic virus-green fluorescent protein in tobacco leaves |
title | An automatic fluorescence phenotyping platform to evaluate dynamic infection process of Tobacco mosaic virus-green fluorescent protein in tobacco leaves |
title_full | An automatic fluorescence phenotyping platform to evaluate dynamic infection process of Tobacco mosaic virus-green fluorescent protein in tobacco leaves |
title_fullStr | An automatic fluorescence phenotyping platform to evaluate dynamic infection process of Tobacco mosaic virus-green fluorescent protein in tobacco leaves |
title_full_unstemmed | An automatic fluorescence phenotyping platform to evaluate dynamic infection process of Tobacco mosaic virus-green fluorescent protein in tobacco leaves |
title_short | An automatic fluorescence phenotyping platform to evaluate dynamic infection process of Tobacco mosaic virus-green fluorescent protein in tobacco leaves |
title_sort | automatic fluorescence phenotyping platform to evaluate dynamic infection process of tobacco mosaic virus-green fluorescent protein in tobacco leaves |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9478445/ https://www.ncbi.nlm.nih.gov/pubmed/36119566 http://dx.doi.org/10.3389/fpls.2022.968855 |
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