Comparing vegetation indices for remote chlorophyll measurement of white poplar and Chinese elm leaves with different adaxial and abaxial surfaces.
Identifieur interne : 001E42 ( Main/Exploration ); précédent : 001E41; suivant : 001E43Comparing vegetation indices for remote chlorophyll measurement of white poplar and Chinese elm leaves with different adaxial and abaxial surfaces.
Auteurs : Shan Lu [République populaire de Chine] ; Xingtong Lu [République populaire de Chine] ; Wenli Zhao [République populaire de Chine] ; Yu Liu [République populaire de Chine] ; Zheyi Wang [République populaire de Chine] ; Kenji Omasa [Japon]Source :
- Journal of experimental botany [ 1460-2431 ] ; 2015.
Descripteurs français
- KwdFr :
- MESH :
- analyse : Chlorophylle.
- méthodes : Spectrophotométrie, Technologie de télédétection.
- physiologie : Feuilles de plante, Populus, Ulmus.
- instrumentation : Spectrophotométrie, Technologie de télédétection.
English descriptors
- KwdEn :
- MESH :
- chemical , analysis : Chlorophyll.
- instrumentation : Remote Sensing Technology, Spectrophotometry.
- methods : Remote Sensing Technology, Spectrophotometry.
- physiology : Plant Leaves, Populus, Ulmus.
Abstract
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, (R719-R726)/(R719-R743), 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.
DOI: 10.1093/jxb/erv270
PubMed: 26034132
PubMed Central: PMC4585420
Affiliations:
- Japon, République populaire de Chine
- Dongbei, Jilin, Région de Kantō
- Changchun, Tokyo
- Université de Tokyo
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first="Xingtong" last="Lu">Xingtong Lu</name><affiliation wicri:level="1"><nlm:affiliation>School of Geographical Sciences, Northeast Normal University, 5268 Renmin Street, Changchun 130024, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Geographical Sciences, Northeast Normal University, 5268 Renmin Street, Changchun 130024</wicri:regionArea><placeName><settlement type="city">Changchun</settlement><region type="province">Jilin</region><region type="groupement">Dongbei</region></placeName></affiliation></author><author><name sortKey="Zhao, Wenli" sort="Zhao, Wenli" uniqKey="Zhao W" first="Wenli" last="Zhao">Wenli Zhao</name><affiliation wicri:level="1"><nlm:affiliation>School of Geographical Sciences, Northeast Normal University, 5268 Renmin Street, Changchun 130024, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Geographical Sciences, Northeast Normal University, 5268 Renmin Street, Changchun 130024</wicri:regionArea><placeName><settlement type="city">Changchun</settlement><region type="province">Jilin</region><region type="groupement">Dongbei</region></placeName></affiliation></author><author><name sortKey="Liu, Yu" sort="Liu, Yu" uniqKey="Liu Y" first="Yu" last="Liu">Yu Liu</name><affiliation wicri:level="1"><nlm:affiliation>School of Geographical Sciences, Northeast Normal University, 5268 Renmin Street, Changchun 130024, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Geographical Sciences, Northeast Normal University, 5268 Renmin Street, Changchun 130024</wicri:regionArea><placeName><settlement type="city">Changchun</settlement><region type="province">Jilin</region><region type="groupement">Dongbei</region></placeName></affiliation></author><author><name sortKey="Wang, Zheyi" sort="Wang, Zheyi" uniqKey="Wang Z" first="Zheyi" last="Wang">Zheyi Wang</name><affiliation wicri:level="1"><nlm:affiliation>School of Geographical Sciences, Northeast Normal University, 5268 Renmin Street, Changchun 130024, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Geographical Sciences, Northeast Normal University, 5268 Renmin Street, Changchun 130024</wicri:regionArea><placeName><settlement type="city">Changchun</settlement><region type="province">Jilin</region><region type="groupement">Dongbei</region></placeName></affiliation></author><author><name sortKey="Omasa, Kenji" sort="Omasa, Kenji" uniqKey="Omasa K" first="Kenji" last="Omasa">Kenji Omasa</name><affiliation wicri:level="4"><nlm:affiliation>Graduate School of Agricultural and Life Sciences, The University of Tokyo, Yayoi 1-1-1, Bunkyo-ku, Tokyo 113-8657, Japan aomasa@mail.ecc.u-tokyo.ac.jp.</nlm:affiliation><country wicri:rule="url">Japon</country><wicri:regionArea>Graduate School of Agricultural and Life Sciences, The University of Tokyo, Yayoi 1-1-1, Bunkyo-ku, Tokyo 113-8657</wicri:regionArea><placeName><settlement type="city">Tokyo</settlement><region type="région">Région de Kantō</region></placeName><orgName type="university">Université de Tokyo</orgName><placeName><settlement type="city">Tokyo</settlement><region type="province">Région de Kantō</region></placeName></affiliation></author></analytic><series><title level="j">Journal of experimental botany</title><idno type="eISSN">1460-2431</idno><imprint><date when="2015" type="published">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Chlorophyll (analysis)</term><term>Plant Leaves (physiology)</term><term>Populus (physiology)</term><term>Remote Sensing Technology (instrumentation)</term><term>Remote Sensing Technology (methods)</term><term>Spectrophotometry (instrumentation)</term><term>Spectrophotometry (methods)</term><term>Ulmus (physiology)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Chlorophylle (analyse)</term><term>Feuilles de plante (physiologie)</term><term>Populus (physiologie)</term><term>Spectrophotométrie (instrumentation)</term><term>Spectrophotométrie (méthodes)</term><term>Technologie de télédétection (instrumentation)</term><term>Technologie de télédétection (méthodes)</term><term>Ulmus (physiologie)</term></keywords><keywords scheme="MESH" type="chemical" qualifier="analysis" xml:lang="en"><term>Chlorophyll</term></keywords><keywords scheme="MESH" qualifier="analyse" xml:lang="fr"><term>Chlorophylle</term></keywords><keywords scheme="MESH" qualifier="instrumentation" xml:lang="en"><term>Remote Sensing Technology</term><term>Spectrophotometry</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Remote Sensing Technology</term><term>Spectrophotometry</term></keywords><keywords scheme="MESH" qualifier="méthodes" xml:lang="fr"><term>Spectrophotométrie</term><term>Technologie de télédétection</term></keywords><keywords scheme="MESH" qualifier="physiologie" xml:lang="fr"><term>Feuilles de plante</term><term>Populus</term><term>Ulmus</term></keywords><keywords scheme="MESH" qualifier="physiology" xml:lang="en"><term>Plant Leaves</term><term>Populus</term><term>Ulmus</term></keywords><keywords scheme="MESH" qualifier="instrumentation" xml:lang="fr"><term>Spectrophotométrie</term><term>Technologie de télédétection</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">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, (R719-R726)/(R719-R743), 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.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">26034132</PMID><DateCompleted><Year>2016</Year><Month>05</Month><Day>16</Day></DateCompleted><DateRevised><Year>2018</Year><Month>11</Month><Day>13</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1460-2431</ISSN><JournalIssue CitedMedium="Internet"><Volume>66</Volume><Issue>18</Issue><PubDate><Year>2015</Year><Month>Sep</Month></PubDate></JournalIssue><Title>Journal of experimental botany</Title><ISOAbbreviation>J Exp Bot</ISOAbbreviation></Journal><ArticleTitle>Comparing vegetation indices for remote chlorophyll measurement of white poplar and Chinese elm leaves with different adaxial and abaxial surfaces.</ArticleTitle><Pagination><MedlinePgn>5625-37</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1093/jxb/erv270</ELocationID><Abstract><AbstractText>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, (R719-R726)/(R719-R743), 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.</AbstractText><CopyrightInformation>© The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Lu</LastName><ForeName>Shan</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>School of Geographical Sciences, Northeast Normal University, 5268 Renmin Street, Changchun 130024, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lu</LastName><ForeName>Xingtong</ForeName><Initials>X</Initials><AffiliationInfo><Affiliation>School of Geographical Sciences, Northeast Normal University, 5268 Renmin Street, Changchun 130024, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zhao</LastName><ForeName>Wenli</ForeName><Initials>W</Initials><AffiliationInfo><Affiliation>School of Geographical Sciences, Northeast Normal University, 5268 Renmin Street, Changchun 130024, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Liu</LastName><ForeName>Yu</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>School of Geographical Sciences, Northeast Normal University, 5268 Renmin Street, Changchun 130024, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wang</LastName><ForeName>Zheyi</ForeName><Initials>Z</Initials><AffiliationInfo><Affiliation>School of Geographical Sciences, Northeast Normal University, 5268 Renmin Street, Changchun 130024, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Omasa</LastName><ForeName>Kenji</ForeName><Initials>K</Initials><AffiliationInfo><Affiliation>Graduate School of Agricultural and Life Sciences, The University of Tokyo, Yayoi 1-1-1, Bunkyo-ku, Tokyo 113-8657, Japan aomasa@mail.ecc.u-tokyo.ac.jp.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D003160">Comparative Study</PublicationType><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2015</Year><Month>06</Month><Day>01</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>J Exp Bot</MedlineTA><NlmUniqueID>9882906</NlmUniqueID><ISSNLinking>0022-0957</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>1406-65-1</RegistryNumber><NameOfSubstance UI="D002734">Chlorophyll</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D002734" MajorTopicYN="N">Chlorophyll</DescriptorName><QualifierName UI="Q000032" MajorTopicYN="Y">analysis</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D018515" MajorTopicYN="N">Plant Leaves</DescriptorName><QualifierName UI="Q000502" MajorTopicYN="N">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D032107" MajorTopicYN="N">Populus</DescriptorName><QualifierName UI="Q000502" MajorTopicYN="Y">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D058998" MajorTopicYN="N">Remote Sensing Technology</DescriptorName><QualifierName UI="Q000295" MajorTopicYN="N">instrumentation</QualifierName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D013053" MajorTopicYN="N">Spectrophotometry</DescriptorName><QualifierName UI="Q000295" MajorTopicYN="N">instrumentation</QualifierName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D034403" MajorTopicYN="N">Ulmus</DescriptorName><QualifierName UI="Q000502" MajorTopicYN="Y">physiology</QualifierName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Adaxial and abaxial leaf surfaces</Keyword><Keyword MajorTopicYN="N">chlorophyll</Keyword><Keyword MajorTopicYN="N">phenotyping</Keyword><Keyword MajorTopicYN="N">reflectance</Keyword><Keyword MajorTopicYN="N">remote sensing</Keyword><Keyword MajorTopicYN="N">vegetation index.</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2015</Year><Month>6</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2015</Year><Month>6</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2016</Year><Month>5</Month><Day>18</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">26034132</ArticleId><ArticleId IdType="pii">erv270</ArticleId><ArticleId IdType="doi">10.1093/jxb/erv270</ArticleId><ArticleId IdType="pmc">PMC4585420</ArticleId></ArticleIdList><ReferenceList><Reference><Citation>Photochem Photobiol Sci. 2007 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sortKey="Lu, Shan" sort="Lu, Shan" uniqKey="Lu S" first="Shan" last="Lu">Shan Lu</name></region><name sortKey="Liu, Yu" sort="Liu, Yu" uniqKey="Liu Y" first="Yu" last="Liu">Yu Liu</name><name sortKey="Lu, Xingtong" sort="Lu, Xingtong" uniqKey="Lu X" first="Xingtong" last="Lu">Xingtong Lu</name><name sortKey="Wang, Zheyi" sort="Wang, Zheyi" uniqKey="Wang Z" first="Zheyi" last="Wang">Zheyi Wang</name><name sortKey="Zhao, Wenli" sort="Zhao, Wenli" uniqKey="Zhao W" first="Wenli" last="Zhao">Wenli Zhao</name></country><country name="Japon"><region name="Région de Kantō"><name sortKey="Omasa, Kenji" sort="Omasa, Kenji" uniqKey="Omasa K" first="Kenji" last="Omasa">Kenji Omasa</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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