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Identification of new cold tolerant Zoysia grass species using high-resolution RGB and multi-spectral imaging

Zoysia grass (Zoysia spp.) is the most widely used warm-season turf grass in Korea due to its durability and resistance to environmental stresses. To develop new longer-period greenness cultivars, it is essential to screen germplasm which maintains the greenness at a lower temperature. Conventional...

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Autores principales: Ku, Ki-Bon, Mansoor, Sheikh, Han, Gyung Deok, Chung, Yong Suk, Tuan, Thai Thanh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10425389/
https://www.ncbi.nlm.nih.gov/pubmed/37580436
http://dx.doi.org/10.1038/s41598-023-40128-2
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author Ku, Ki-Bon
Mansoor, Sheikh
Han, Gyung Deok
Chung, Yong Suk
Tuan, Thai Thanh
author_facet Ku, Ki-Bon
Mansoor, Sheikh
Han, Gyung Deok
Chung, Yong Suk
Tuan, Thai Thanh
author_sort Ku, Ki-Bon
collection PubMed
description Zoysia grass (Zoysia spp.) is the most widely used warm-season turf grass in Korea due to its durability and resistance to environmental stresses. To develop new longer-period greenness cultivars, it is essential to screen germplasm which maintains the greenness at a lower temperature. Conventional methods are time-consuming, laborious, and subjective. Therefore, in this study, we demonstrate an objective and efficient method to screen maintaining longer greenness germplasm using RGB and multispectral images. From August to December, time-series data were acquired and we calculated green cover percentage (GCP), Normalized Difference Vegetation Index (NDVI), Normalized Difference Red Edge Index (NDRE), Soil-adjusted Vegetation Index (SAVI), and Enhanced Vegetation Index (EVI) values of germplasm from RGB and multispectral images by applying vegetation indexs. The result showed significant differences in GCP, NDVI, NDRE, SAVI, and EVI among germplasm (p < 0.05). The GCP, which evaluated the quantity of greenness by counting pixels of the green area from RGB images, exhibited maintenance of greenness over 90% for August and September but, sharply decrease from October. The study found significant differences in GCP and NDVI among germplasm. san208 exhibiting over 90% GCP and high NDVI values during 153 days. In addition, we also conducted assessments using various vegetation indexes, namely NDRE, SAVI, and EVI. san208 exhibited NDRE levels exceeding 3% throughout this period. As for SAVI, it initially started at approximately 38% and gradually decreased to around 4% over the course of these days. Furthermore, for the month of August, it recorded approximately 6%, but experienced a decline from about 9% to 1% between September and October. The complementary use of both indicators could be an efficient method for objectively assessing the greenness of turf both quantitatively and qualitatively.
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spelling pubmed-104253892023-08-16 Identification of new cold tolerant Zoysia grass species using high-resolution RGB and multi-spectral imaging Ku, Ki-Bon Mansoor, Sheikh Han, Gyung Deok Chung, Yong Suk Tuan, Thai Thanh Sci Rep Article Zoysia grass (Zoysia spp.) is the most widely used warm-season turf grass in Korea due to its durability and resistance to environmental stresses. To develop new longer-period greenness cultivars, it is essential to screen germplasm which maintains the greenness at a lower temperature. Conventional methods are time-consuming, laborious, and subjective. Therefore, in this study, we demonstrate an objective and efficient method to screen maintaining longer greenness germplasm using RGB and multispectral images. From August to December, time-series data were acquired and we calculated green cover percentage (GCP), Normalized Difference Vegetation Index (NDVI), Normalized Difference Red Edge Index (NDRE), Soil-adjusted Vegetation Index (SAVI), and Enhanced Vegetation Index (EVI) values of germplasm from RGB and multispectral images by applying vegetation indexs. The result showed significant differences in GCP, NDVI, NDRE, SAVI, and EVI among germplasm (p < 0.05). The GCP, which evaluated the quantity of greenness by counting pixels of the green area from RGB images, exhibited maintenance of greenness over 90% for August and September but, sharply decrease from October. The study found significant differences in GCP and NDVI among germplasm. san208 exhibiting over 90% GCP and high NDVI values during 153 days. In addition, we also conducted assessments using various vegetation indexes, namely NDRE, SAVI, and EVI. san208 exhibited NDRE levels exceeding 3% throughout this period. As for SAVI, it initially started at approximately 38% and gradually decreased to around 4% over the course of these days. Furthermore, for the month of August, it recorded approximately 6%, but experienced a decline from about 9% to 1% between September and October. The complementary use of both indicators could be an efficient method for objectively assessing the greenness of turf both quantitatively and qualitatively. Nature Publishing Group UK 2023-08-14 /pmc/articles/PMC10425389/ /pubmed/37580436 http://dx.doi.org/10.1038/s41598-023-40128-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Ku, Ki-Bon
Mansoor, Sheikh
Han, Gyung Deok
Chung, Yong Suk
Tuan, Thai Thanh
Identification of new cold tolerant Zoysia grass species using high-resolution RGB and multi-spectral imaging
title Identification of new cold tolerant Zoysia grass species using high-resolution RGB and multi-spectral imaging
title_full Identification of new cold tolerant Zoysia grass species using high-resolution RGB and multi-spectral imaging
title_fullStr Identification of new cold tolerant Zoysia grass species using high-resolution RGB and multi-spectral imaging
title_full_unstemmed Identification of new cold tolerant Zoysia grass species using high-resolution RGB and multi-spectral imaging
title_short Identification of new cold tolerant Zoysia grass species using high-resolution RGB and multi-spectral imaging
title_sort identification of new cold tolerant zoysia grass species using high-resolution rgb and multi-spectral imaging
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10425389/
https://www.ncbi.nlm.nih.gov/pubmed/37580436
http://dx.doi.org/10.1038/s41598-023-40128-2
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