Method for automatically identifying spectra of different wood cell wall layers in Raman imaging data set.
Identifieur interne : 001C52 ( Main/Exploration ); précédent : 001C51; suivant : 001C53Method for automatically identifying spectra of different wood cell wall layers in Raman imaging data set.
Auteurs : Xun Zhang [République populaire de Chine] ; Zhe Ji ; Xia Zhou ; Jian-Feng Ma ; Ya-Hong Hu ; Feng XuSource :
- Analytical chemistry [ 1520-6882 ] ; 2015.
Descripteurs français
- KwdFr :
- Analyse de regroupements (MeSH), Analyse en composantes principales (MeSH), Analyse spectrale Raman (méthodes), Bois (composition chimique), Bois (ultrastructure), Cellulose (analyse), Lignine (analyse), Microscopie (méthodes), Paroi cellulaire (composition chimique), Paroi cellulaire (ultrastructure), Populus (composition chimique), Populus (cytologie), Populus (ultrastructure).
- MESH :
- analyse : Cellulose, Lignine.
- composition chimique : Bois, Paroi cellulaire, Populus.
- cytologie : Populus.
- méthodes : Analyse spectrale Raman, Microscopie.
- ultrastructure : Analyse de regroupements, Analyse en composantes principales, Bois, Paroi cellulaire, Populus.
English descriptors
- KwdEn :
- Cell Wall (chemistry), Cell Wall (ultrastructure), Cellulose (analysis), Cluster Analysis (MeSH), Lignin (analysis), Microscopy (methods), Populus (chemistry), Populus (cytology), Populus (ultrastructure), Principal Component Analysis (MeSH), Spectrum Analysis, Raman (methods), Wood (chemistry), Wood (ultrastructure).
- MESH :
- chemical , analysis : Cellulose, Lignin.
- chemistry : Cell Wall, Populus, Wood.
- cytology : Populus.
- methods : Microscopy, Spectrum Analysis, Raman.
- ultrastructure : Cell Wall, Populus, Wood.
- Cluster Analysis, Principal Component Analysis.
Abstract
The technique of Raman spectroscopic imaging is finding ever-increasing applications in the field of wood science for its ability to provide spatial and spectral information about the sample. On the basis of the acquired Raman imaging data set, it is possible to determine the distribution of chemical components in various wood cell wall layers. However, the Raman imaging data set often contains thousands of spectra measured at hundreds or even thousands of individual frequencies, which results in difficulties accurately and quickly extracting all of the spectra within a specific morphological region of wood cell walls. To address this issue, the authors propose a new method to automatically identify Raman spectra of different cell wall layers on the basis of principal component analysis (PCA) and cluster analysis. A Raman imaging data set collected from a 55.5 μm × 47.5 μm cross-section of poplar tension wood was analyzed. Several thousand spectra were successfully classified into five groups in accordance with different morphological regions, namely, cell corner (CC), compound middle lamella (CML), secondary wall (SW), gelatinous layer (G-layer), and cell lumen. Their corresponding average spectra were also calculated. In addition, the relationship between different characteristic peaks in the obtained Raman spectra was estimated and it was found that the peak at 1331 cm(-1) is more related to lignin rather than cellulose. Not only can this novel method provide a convenient and accurate procedure for identifying the spectra of different cell wall layers in a Raman imaging data set, but it also can bring new insights into studying the morphology and topochemistry in wood cell walls.
DOI: 10.1021/ac504144s
PubMed: 25531490
Affiliations:
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Feng" uniqKey="Ma J" first="Jian-Feng" last="Ma">Jian-Feng Ma</name></author><author><name sortKey="Hu, Ya Hong" sort="Hu, Ya Hong" uniqKey="Hu Y" first="Ya-Hong" last="Hu">Ya-Hong Hu</name></author><author><name sortKey="Xu, Feng" sort="Xu, Feng" uniqKey="Xu F" first="Feng" last="Xu">Feng Xu</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2015">2015</date><idno type="RBID">pubmed:25531490</idno><idno type="pmid">25531490</idno><idno type="doi">10.1021/ac504144s</idno><idno type="wicri:Area/Main/Corpus">001E65</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">001E65</idno><idno type="wicri:Area/Main/Curation">001E65</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Curation">001E65</idno><idno type="wicri:Area/Main/Exploration">001E65</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Method for automatically identifying spectra of different wood cell wall layers in Raman imaging data set.</title><author><name sortKey="Zhang, Xun" sort="Zhang, Xun" uniqKey="Zhang X" first="Xun" last="Zhang">Xun Zhang</name><affiliation wicri:level="1"><nlm:affiliation>Beijing Key Laboratory of Lignocellulosic Chemistry, Beijing Forestry University , Beijing, 100083, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Beijing Key Laboratory of Lignocellulosic Chemistry, Beijing Forestry University , Beijing, 100083</wicri:regionArea><wicri:noRegion>100083</wicri:noRegion></affiliation></author><author><name sortKey="Ji, Zhe" sort="Ji, Zhe" uniqKey="Ji Z" first="Zhe" last="Ji">Zhe Ji</name></author><author><name sortKey="Zhou, Xia" sort="Zhou, Xia" uniqKey="Zhou X" first="Xia" last="Zhou">Xia Zhou</name></author><author><name sortKey="Ma, Jian Feng" sort="Ma, Jian Feng" uniqKey="Ma J" first="Jian-Feng" last="Ma">Jian-Feng Ma</name></author><author><name sortKey="Hu, Ya Hong" sort="Hu, Ya Hong" uniqKey="Hu Y" first="Ya-Hong" last="Hu">Ya-Hong Hu</name></author><author><name sortKey="Xu, Feng" sort="Xu, Feng" uniqKey="Xu F" first="Feng" last="Xu">Feng Xu</name></author></analytic><series><title level="j">Analytical chemistry</title><idno type="eISSN">1520-6882</idno><imprint><date when="2015" type="published">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Cell Wall (chemistry)</term><term>Cell Wall (ultrastructure)</term><term>Cellulose (analysis)</term><term>Cluster Analysis (MeSH)</term><term>Lignin (analysis)</term><term>Microscopy (methods)</term><term>Populus (chemistry)</term><term>Populus (cytology)</term><term>Populus (ultrastructure)</term><term>Principal Component Analysis (MeSH)</term><term>Spectrum Analysis, Raman (methods)</term><term>Wood (chemistry)</term><term>Wood (ultrastructure)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Analyse de regroupements (MeSH)</term><term>Analyse en composantes principales (MeSH)</term><term>Analyse spectrale Raman (méthodes)</term><term>Bois (composition chimique)</term><term>Bois (ultrastructure)</term><term>Cellulose (analyse)</term><term>Lignine (analyse)</term><term>Microscopie (méthodes)</term><term>Paroi cellulaire (composition chimique)</term><term>Paroi cellulaire (ultrastructure)</term><term>Populus (composition chimique)</term><term>Populus (cytologie)</term><term>Populus (ultrastructure)</term></keywords><keywords scheme="MESH" type="chemical" qualifier="analysis" xml:lang="en"><term>Cellulose</term><term>Lignin</term></keywords><keywords scheme="MESH" qualifier="analyse" xml:lang="fr"><term>Cellulose</term><term>Lignine</term></keywords><keywords scheme="MESH" qualifier="chemistry" xml:lang="en"><term>Cell Wall</term><term>Populus</term><term>Wood</term></keywords><keywords scheme="MESH" qualifier="composition chimique" xml:lang="fr"><term>Bois</term><term>Paroi cellulaire</term><term>Populus</term></keywords><keywords scheme="MESH" qualifier="cytologie" xml:lang="fr"><term>Populus</term></keywords><keywords scheme="MESH" qualifier="cytology" xml:lang="en"><term>Populus</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Microscopy</term><term>Spectrum Analysis, Raman</term></keywords><keywords scheme="MESH" qualifier="méthodes" xml:lang="fr"><term>Analyse spectrale Raman</term><term>Microscopie</term></keywords><keywords scheme="MESH" qualifier="ultrastructure" xml:lang="en"><term>Cell Wall</term><term>Populus</term><term>Wood</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Cluster Analysis</term><term>Principal Component Analysis</term></keywords><keywords scheme="MESH" qualifier="ultrastructure" xml:lang="fr"><term>Analyse de regroupements</term><term>Analyse en composantes principales</term><term>Bois</term><term>Paroi cellulaire</term><term>Populus</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The technique of Raman spectroscopic imaging is finding ever-increasing applications in the field of wood science for its ability to provide spatial and spectral information about the sample. On the basis of the acquired Raman imaging data set, it is possible to determine the distribution of chemical components in various wood cell wall layers. However, the Raman imaging data set often contains thousands of spectra measured at hundreds or even thousands of individual frequencies, which results in difficulties accurately and quickly extracting all of the spectra within a specific morphological region of wood cell walls. To address this issue, the authors propose a new method to automatically identify Raman spectra of different cell wall layers on the basis of principal component analysis (PCA) and cluster analysis. A Raman imaging data set collected from a 55.5 μm × 47.5 μm cross-section of poplar tension wood was analyzed. Several thousand spectra were successfully classified into five groups in accordance with different morphological regions, namely, cell corner (CC), compound middle lamella (CML), secondary wall (SW), gelatinous layer (G-layer), and cell lumen. Their corresponding average spectra were also calculated. In addition, the relationship between different characteristic peaks in the obtained Raman spectra was estimated and it was found that the peak at 1331 cm(-1) is more related to lignin rather than cellulose. Not only can this novel method provide a convenient and accurate procedure for identifying the spectra of different cell wall layers in a Raman imaging data set, but it also can bring new insights into studying the morphology and topochemistry in wood cell walls. </div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">25531490</PMID><DateCompleted><Year>2015</Year><Month>11</Month><Day>05</Day></DateCompleted><DateRevised><Year>2015</Year><Month>01</Month><Day>21</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1520-6882</ISSN><JournalIssue CitedMedium="Internet"><Volume>87</Volume><Issue>2</Issue><PubDate><Year>2015</Year><Month>Jan</Month><Day>20</Day></PubDate></JournalIssue><Title>Analytical chemistry</Title><ISOAbbreviation>Anal Chem</ISOAbbreviation></Journal><ArticleTitle>Method for automatically identifying spectra of different wood cell wall layers in Raman imaging data set.</ArticleTitle><Pagination><MedlinePgn>1344-50</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1021/ac504144s</ELocationID><Abstract><AbstractText>The technique of Raman spectroscopic imaging is finding ever-increasing applications in the field of wood science for its ability to provide spatial and spectral information about the sample. On the basis of the acquired Raman imaging data set, it is possible to determine the distribution of chemical components in various wood cell wall layers. However, the Raman imaging data set often contains thousands of spectra measured at hundreds or even thousands of individual frequencies, which results in difficulties accurately and quickly extracting all of the spectra within a specific morphological region of wood cell walls. To address this issue, the authors propose a new method to automatically identify Raman spectra of different cell wall layers on the basis of principal component analysis (PCA) and cluster analysis. A Raman imaging data set collected from a 55.5 μm × 47.5 μm cross-section of poplar tension wood was analyzed. Several thousand spectra were successfully classified into five groups in accordance with different morphological regions, namely, cell corner (CC), compound middle lamella (CML), secondary wall (SW), gelatinous layer (G-layer), and cell lumen. Their corresponding average spectra were also calculated. In addition, the relationship between different characteristic peaks in the obtained Raman spectra was estimated and it was found that the peak at 1331 cm(-1) is more related to lignin rather than cellulose. Not only can this novel method provide a convenient and accurate procedure for identifying the spectra of different cell wall layers in a Raman imaging data set, but it also can bring new insights into studying the morphology and topochemistry in wood cell walls. </AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Zhang</LastName><ForeName>Xun</ForeName><Initials>X</Initials><AffiliationInfo><Affiliation>Beijing Key Laboratory of Lignocellulosic Chemistry, Beijing Forestry University , Beijing, 100083, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ji</LastName><ForeName>Zhe</ForeName><Initials>Z</Initials></Author><Author ValidYN="Y"><LastName>Zhou</LastName><ForeName>Xia</ForeName><Initials>X</Initials></Author><Author ValidYN="Y"><LastName>Ma</LastName><ForeName>Jian-Feng</ForeName><Initials>JF</Initials></Author><Author ValidYN="Y"><LastName>Hu</LastName><ForeName>Ya-Hong</ForeName><Initials>YH</Initials></Author><Author ValidYN="Y"><LastName>Xu</LastName><ForeName>Feng</ForeName><Initials>F</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><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>01</Month><Day>08</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>Anal Chem</MedlineTA><NlmUniqueID>0370536</NlmUniqueID><ISSNLinking>0003-2700</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>9004-34-6</RegistryNumber><NameOfSubstance UI="D002482">Cellulose</NameOfSubstance></Chemical><Chemical><RegistryNumber>9005-53-2</RegistryNumber><NameOfSubstance UI="D008031">Lignin</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D002473" MajorTopicYN="N">Cell Wall</DescriptorName><QualifierName UI="Q000737" MajorTopicYN="Y">chemistry</QualifierName><QualifierName UI="Q000648" MajorTopicYN="Y">ultrastructure</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D002482" MajorTopicYN="N">Cellulose</DescriptorName><QualifierName UI="Q000032" MajorTopicYN="N">analysis</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D016000" MajorTopicYN="N">Cluster Analysis</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008031" MajorTopicYN="N">Lignin</DescriptorName><QualifierName UI="Q000032" MajorTopicYN="N">analysis</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D008853" MajorTopicYN="N">Microscopy</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D032107" MajorTopicYN="N">Populus</DescriptorName><QualifierName UI="Q000737" MajorTopicYN="Y">chemistry</QualifierName><QualifierName UI="Q000166" 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PubStatus="medline"><Year>2015</Year><Month>11</Month><Day>6</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">25531490</ArticleId><ArticleId IdType="doi">10.1021/ac504144s</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>République populaire de Chine</li></country></list><tree><noCountry><name sortKey="Hu, Ya Hong" sort="Hu, Ya Hong" uniqKey="Hu Y" first="Ya-Hong" last="Hu">Ya-Hong Hu</name><name sortKey="Ji, Zhe" sort="Ji, Zhe" uniqKey="Ji Z" first="Zhe" last="Ji">Zhe Ji</name><name sortKey="Ma, Jian Feng" sort="Ma, Jian Feng" uniqKey="Ma J" first="Jian-Feng" last="Ma">Jian-Feng Ma</name><name sortKey="Xu, Feng" sort="Xu, Feng" uniqKey="Xu F" first="Feng" last="Xu">Feng Xu</name><name sortKey="Zhou, Xia" sort="Zhou, Xia" uniqKey="Zhou X" first="Xia" last="Zhou">Xia Zhou</name></noCountry><country name="République populaire de Chine"><noRegion><name sortKey="Zhang, Xun" sort="Zhang, Xun" uniqKey="Zhang X" first="Xun" last="Zhang">Xun Zhang</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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