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Comparing vegetation indices for remote chlorophyll measurement of white poplar and Chinese elm leaves with different adaxial and abaxial surfaces
Quick non-destructive assessment of leaf chlorophyll content (LCC) is important for studying phenotypes related to plant growth and stress resistance. This study was undertaken to investigate the quantitative relationship between LCC and different vegetation indices (VIs) on both adaxial and abaxial...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4585420/ https://www.ncbi.nlm.nih.gov/pubmed/26034132 http://dx.doi.org/10.1093/jxb/erv270 |
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author | Lu, Shan Lu, Xingtong Zhao, Wenli Liu, Yu Wang, Zheyi Omasa, Kenji |
author_facet | Lu, Shan Lu, Xingtong Zhao, Wenli Liu, Yu Wang, Zheyi Omasa, Kenji |
author_sort | Lu, Shan |
collection | PubMed |
description | Quick non-destructive assessment of leaf chlorophyll content (LCC) is important for studying phenotypes related to plant growth and stress resistance. This study was undertaken to investigate the quantitative relationship between LCC and different vegetation indices (VIs) on both adaxial and abaxial surfaces of white poplar (Populus alba), which has dense tubular hairs on its abaxial surface, and Chinese elm (Ulmus pumila var. pendula), which does not show obvious superficial differences except for lighter colour on the abaxial surface. Some published and newly developed VIs were tested to relate them to LCC. The results showed that most of the published VIs had strong relationships with LCC on the one-surface dataset, but did not show a clear relationship with LCC when both adaxial and abaxial surface reflectance data were included. Among the reflectance indices tested, the modified Datt index, (R (719)−R (726))/(R (719)−R (743)), performed best and is proposed as a new index for remote estimation of chlorophyll content in plants with varying leaf surface structures. It explained 92% of LCC variation in this research, and the root mean square error of the LCC prediction was 5.23 μg/cm(2). This new index is insensitive to the effects of adaxial and abaxial leaf surface structures and is strongly related to the variation in reflectance caused by chlorophyll content. |
format | Online Article Text |
id | pubmed-4585420 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-45854202015-09-29 Comparing vegetation indices for remote chlorophyll measurement of white poplar and Chinese elm leaves with different adaxial and abaxial surfaces Lu, Shan Lu, Xingtong Zhao, Wenli Liu, Yu Wang, Zheyi Omasa, Kenji J Exp Bot Research Paper Quick non-destructive assessment of leaf chlorophyll content (LCC) is important for studying phenotypes related to plant growth and stress resistance. This study was undertaken to investigate the quantitative relationship between LCC and different vegetation indices (VIs) on both adaxial and abaxial surfaces of white poplar (Populus alba), which has dense tubular hairs on its abaxial surface, and Chinese elm (Ulmus pumila var. pendula), which does not show obvious superficial differences except for lighter colour on the abaxial surface. Some published and newly developed VIs were tested to relate them to LCC. The results showed that most of the published VIs had strong relationships with LCC on the one-surface dataset, but did not show a clear relationship with LCC when both adaxial and abaxial surface reflectance data were included. Among the reflectance indices tested, the modified Datt index, (R (719)−R (726))/(R (719)−R (743)), performed best and is proposed as a new index for remote estimation of chlorophyll content in plants with varying leaf surface structures. It explained 92% of LCC variation in this research, and the root mean square error of the LCC prediction was 5.23 μg/cm(2). This new index is insensitive to the effects of adaxial and abaxial leaf surface structures and is strongly related to the variation in reflectance caused by chlorophyll content. Oxford University Press 2015-09 2015-06-01 /pmc/articles/PMC4585420/ /pubmed/26034132 http://dx.doi.org/10.1093/jxb/erv270 Text en © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology. http://creativecommons.org/licenses/by/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Paper Lu, Shan Lu, Xingtong Zhao, Wenli Liu, Yu Wang, Zheyi Omasa, Kenji Comparing vegetation indices for remote chlorophyll measurement of white poplar and Chinese elm leaves with different adaxial and abaxial surfaces |
title | Comparing vegetation indices for remote chlorophyll measurement of white poplar and Chinese elm leaves with different adaxial and abaxial surfaces |
title_full | Comparing vegetation indices for remote chlorophyll measurement of white poplar and Chinese elm leaves with different adaxial and abaxial surfaces |
title_fullStr | Comparing vegetation indices for remote chlorophyll measurement of white poplar and Chinese elm leaves with different adaxial and abaxial surfaces |
title_full_unstemmed | Comparing vegetation indices for remote chlorophyll measurement of white poplar and Chinese elm leaves with different adaxial and abaxial surfaces |
title_short | Comparing vegetation indices for remote chlorophyll measurement of white poplar and Chinese elm leaves with different adaxial and abaxial surfaces |
title_sort | comparing vegetation indices for remote chlorophyll measurement of white poplar and chinese elm leaves with different adaxial and abaxial surfaces |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4585420/ https://www.ncbi.nlm.nih.gov/pubmed/26034132 http://dx.doi.org/10.1093/jxb/erv270 |
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