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Genetic Dissection of Seasonal Changes in a Greening Plant Based on Time-Series Multispectral Imaging
Good appearance throughout the year is important for perennial ornamental plants used for rooftop greenery. However, the methods for evaluating appearance throughout the year, such as plant color and growth activity, are not well understood. In this study, evergreen and winter-dormant parents of Phe...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10610531/ https://www.ncbi.nlm.nih.gov/pubmed/37896060 http://dx.doi.org/10.3390/plants12203597 |
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author | Koji, Taeko Iwata, Hiroyoshi Ishimori, Motoyuki Takanashi, Hideki Yamasaki, Yuji Tsujimoto, Hisashi |
author_facet | Koji, Taeko Iwata, Hiroyoshi Ishimori, Motoyuki Takanashi, Hideki Yamasaki, Yuji Tsujimoto, Hisashi |
author_sort | Koji, Taeko |
collection | PubMed |
description | Good appearance throughout the year is important for perennial ornamental plants used for rooftop greenery. However, the methods for evaluating appearance throughout the year, such as plant color and growth activity, are not well understood. In this study, evergreen and winter-dormant parents of Phedimus takesimensis and 94 F(1) plants were used for multispectral imaging. We took 16 multispectral image measurements from March 2019 to April 2020 and used them to calculate 15 vegetation indices and the area of plant cover. QTL analysis was also performed. Traits such as the area of plant cover and vegetation indices related to biomass were high during spring and summer (growth period), whereas vegetation indices related to anthocyanins were high in winter (dormancy period). According to the PCA, changes in the intensity of light reflected from the plants at different wavelengths over the course of a year were consistent with the changes in plant color and growth activity. Seven QTLs were found to be associated with major seasonal growth changes. This approach, which monitors not only at a single point in time but also over time, can reveal morphological changes during growth, senescence, and dormancy throughout the year. |
format | Online Article Text |
id | pubmed-10610531 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-106105312023-10-28 Genetic Dissection of Seasonal Changes in a Greening Plant Based on Time-Series Multispectral Imaging Koji, Taeko Iwata, Hiroyoshi Ishimori, Motoyuki Takanashi, Hideki Yamasaki, Yuji Tsujimoto, Hisashi Plants (Basel) Article Good appearance throughout the year is important for perennial ornamental plants used for rooftop greenery. However, the methods for evaluating appearance throughout the year, such as plant color and growth activity, are not well understood. In this study, evergreen and winter-dormant parents of Phedimus takesimensis and 94 F(1) plants were used for multispectral imaging. We took 16 multispectral image measurements from March 2019 to April 2020 and used them to calculate 15 vegetation indices and the area of plant cover. QTL analysis was also performed. Traits such as the area of plant cover and vegetation indices related to biomass were high during spring and summer (growth period), whereas vegetation indices related to anthocyanins were high in winter (dormancy period). According to the PCA, changes in the intensity of light reflected from the plants at different wavelengths over the course of a year were consistent with the changes in plant color and growth activity. Seven QTLs were found to be associated with major seasonal growth changes. This approach, which monitors not only at a single point in time but also over time, can reveal morphological changes during growth, senescence, and dormancy throughout the year. MDPI 2023-10-17 /pmc/articles/PMC10610531/ /pubmed/37896060 http://dx.doi.org/10.3390/plants12203597 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Koji, Taeko Iwata, Hiroyoshi Ishimori, Motoyuki Takanashi, Hideki Yamasaki, Yuji Tsujimoto, Hisashi Genetic Dissection of Seasonal Changes in a Greening Plant Based on Time-Series Multispectral Imaging |
title | Genetic Dissection of Seasonal Changes in a Greening Plant Based on Time-Series Multispectral Imaging |
title_full | Genetic Dissection of Seasonal Changes in a Greening Plant Based on Time-Series Multispectral Imaging |
title_fullStr | Genetic Dissection of Seasonal Changes in a Greening Plant Based on Time-Series Multispectral Imaging |
title_full_unstemmed | Genetic Dissection of Seasonal Changes in a Greening Plant Based on Time-Series Multispectral Imaging |
title_short | Genetic Dissection of Seasonal Changes in a Greening Plant Based on Time-Series Multispectral Imaging |
title_sort | genetic dissection of seasonal changes in a greening plant based on time-series multispectral imaging |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10610531/ https://www.ncbi.nlm.nih.gov/pubmed/37896060 http://dx.doi.org/10.3390/plants12203597 |
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