An integrated approach utilising chemometrics and GC/MS for classification of chamomile flowers, essential oils and commercial products
•Three types of chamomile flowers, commercial products and oils were analysed.•A sample class prediction (SCP) model was constructed based on chemometrics.•Commercial products and oils containing chamomile were predicted by the SCP model.•Identification of markers correlated with different chamomile...
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| Veröffentlicht in: | Food chemistry 2014-06, Vol.152, p.391-398 |
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| creator | Wang, Mei Avula, Bharathi Wang, Yan-Hong Zhao, Jianping Avonto, Cristina Parcher, Jon F. Raman, Vijayasankar Zweigenbaum, Jerry A. Wylie, Philip L. Khan, Ikhlas A. |
| description | •Three types of chamomile flowers, commercial products and oils were analysed.•A sample class prediction (SCP) model was constructed based on chemometrics.•Commercial products and oils containing chamomile were predicted by the SCP model.•Identification of markers correlated with different chamomiles was explored.
As part of an ongoing research program on authentication, safety and biological evaluation of phytochemicals and dietary supplements, an in-depth chemical investigation of different types of chamomile was performed. A collection of chamomile samples including authenticated plants, commercial products and essential oils was analysed by GC/MS. Twenty-seven authenticated plant samples representing three types of chamomile, viz. German chamomile, Roman chamomile and Juhua were analysed. This set of data was employed to construct a sample class prediction (SCP) model based on stepwise reduction of data dimensionality followed by principle component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The model was cross-validated with samples including authenticated plants and commercial products. The model demonstrated 100.0% accuracy for both recognition and prediction abilities. In addition, 35 commercial products and 11 essential oils purported to contain chamomile were subsequently predicted by the validated PLS-DA model. Furthermore, tentative identification of the marker compounds correlated with different types of chamomile was explored. |
| doi_str_mv | 10.1016/j.foodchem.2013.11.118 |
| format | Article |
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As part of an ongoing research program on authentication, safety and biological evaluation of phytochemicals and dietary supplements, an in-depth chemical investigation of different types of chamomile was performed. A collection of chamomile samples including authenticated plants, commercial products and essential oils was analysed by GC/MS. Twenty-seven authenticated plant samples representing three types of chamomile, viz. German chamomile, Roman chamomile and Juhua were analysed. This set of data was employed to construct a sample class prediction (SCP) model based on stepwise reduction of data dimensionality followed by principle component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The model was cross-validated with samples including authenticated plants and commercial products. The model demonstrated 100.0% accuracy for both recognition and prediction abilities. In addition, 35 commercial products and 11 essential oils purported to contain chamomile were subsequently predicted by the validated PLS-DA model. Furthermore, tentative identification of the marker compounds correlated with different types of chamomile was explored.</description><identifier>ISSN: 0308-8146</identifier><identifier>EISSN: 1873-7072</identifier><identifier>DOI: 10.1016/j.foodchem.2013.11.118</identifier><identifier>PMID: 24444953</identifier><identifier>CODEN: FOCHDJ</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Biological and medical sciences ; Chamaemelum nobile ; Chamomile - chemistry ; Chamomile - classification ; Chemometric analysis ; Chrysanthemum morifolium ; Discriminant Analysis ; Flowers - chemistry ; Flowers - classification ; Gas Chromatography-Mass Spectrometry - methods ; General pharmacology ; Matricaria chamomilla ; Medical sciences ; Oils, Volatile - chemistry ; Pharmacognosy. Homeopathy. Health food ; Pharmacology. Drug treatments ; Plant Extracts - chemistry ; Sample class prediction model</subject><ispartof>Food chemistry, 2014-06, Vol.152, p.391-398</ispartof><rights>2013 Elsevier Ltd</rights><rights>2015 INIST-CNRS</rights><rights>Copyright © 2013 Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c431t-5fb0632d0422f74d80fbeb7275a34a001ee217337c3e41c757257156d3c6fb523</citedby><cites>FETCH-LOGICAL-c431t-5fb0632d0422f74d80fbeb7275a34a001ee217337c3e41c757257156d3c6fb523</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0308814613018062$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28351937$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24444953$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wang, Mei</creatorcontrib><creatorcontrib>Avula, Bharathi</creatorcontrib><creatorcontrib>Wang, Yan-Hong</creatorcontrib><creatorcontrib>Zhao, Jianping</creatorcontrib><creatorcontrib>Avonto, Cristina</creatorcontrib><creatorcontrib>Parcher, Jon F.</creatorcontrib><creatorcontrib>Raman, Vijayasankar</creatorcontrib><creatorcontrib>Zweigenbaum, Jerry A.</creatorcontrib><creatorcontrib>Wylie, Philip L.</creatorcontrib><creatorcontrib>Khan, Ikhlas A.</creatorcontrib><title>An integrated approach utilising chemometrics and GC/MS for classification of chamomile flowers, essential oils and commercial products</title><title>Food chemistry</title><addtitle>Food Chem</addtitle><description>•Three types of chamomile flowers, commercial products and oils were analysed.•A sample class prediction (SCP) model was constructed based on chemometrics.•Commercial products and oils containing chamomile were predicted by the SCP model.•Identification of markers correlated with different chamomiles was explored.
As part of an ongoing research program on authentication, safety and biological evaluation of phytochemicals and dietary supplements, an in-depth chemical investigation of different types of chamomile was performed. A collection of chamomile samples including authenticated plants, commercial products and essential oils was analysed by GC/MS. Twenty-seven authenticated plant samples representing three types of chamomile, viz. German chamomile, Roman chamomile and Juhua were analysed. This set of data was employed to construct a sample class prediction (SCP) model based on stepwise reduction of data dimensionality followed by principle component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The model was cross-validated with samples including authenticated plants and commercial products. The model demonstrated 100.0% accuracy for both recognition and prediction abilities. In addition, 35 commercial products and 11 essential oils purported to contain chamomile were subsequently predicted by the validated PLS-DA model. Furthermore, tentative identification of the marker compounds correlated with different types of chamomile was explored.</description><subject>Biological and medical sciences</subject><subject>Chamaemelum nobile</subject><subject>Chamomile - chemistry</subject><subject>Chamomile - classification</subject><subject>Chemometric analysis</subject><subject>Chrysanthemum morifolium</subject><subject>Discriminant Analysis</subject><subject>Flowers - chemistry</subject><subject>Flowers - classification</subject><subject>Gas Chromatography-Mass Spectrometry - methods</subject><subject>General pharmacology</subject><subject>Matricaria chamomilla</subject><subject>Medical sciences</subject><subject>Oils, Volatile - chemistry</subject><subject>Pharmacognosy. Homeopathy. Health food</subject><subject>Pharmacology. Drug treatments</subject><subject>Plant Extracts - chemistry</subject><subject>Sample class prediction model</subject><issn>0308-8146</issn><issn>1873-7072</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkc9u1DAQxi0EotvCK1S-IHEgW_9J4uyNagUtUhEH4Gx57XHrlRMvHgfEE_DaONotHGuNZGn0m_lG30fIJWdrznh_tV_7lJx9gHEtGJdrzmsNz8iKD0o2iinxnKyYZEMz8LY_I-eIe8ZYZYeX5Ey09W06uSJ_ricapgL32RRw1BwOORn7QOcSYsAw3dNFI41QcrBIzeTozfbq81fqU6Y2GsTggzUlpIkmX2FT4RCB-ph-QcZ3FBBhKsFEmkI8brBpHCHbpVfl3GwLviIvvIkIr0__Bfn-8cO37W1z9-Xm0_b6rrGt5KXp_I71UjjWCuFV6wbmd7BTQnVGtoYxDiC4klJZCS23qlOiU7zrnbS933VCXpC3x71V-McMWPQY0EKMZoI0o-Zd9YZxxdqn0XYj-uruRlW0P6I2J8QMXh9yGE3-rTnTS156rx_z0ktemvNaQx28PGnMuxHcv7HHgCrw5gQYtCb6bCYb8D83yI5v5HLB-yMH1byfAbJGG2Cy4EIGW7RL4alb_gJVvbfq</recordid><startdate>20140601</startdate><enddate>20140601</enddate><creator>Wang, Mei</creator><creator>Avula, Bharathi</creator><creator>Wang, Yan-Hong</creator><creator>Zhao, Jianping</creator><creator>Avonto, Cristina</creator><creator>Parcher, Jon F.</creator><creator>Raman, Vijayasankar</creator><creator>Zweigenbaum, Jerry A.</creator><creator>Wylie, Philip L.</creator><creator>Khan, Ikhlas A.</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7QR</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope></search><sort><creationdate>20140601</creationdate><title>An integrated approach utilising chemometrics and GC/MS for classification of chamomile flowers, essential oils and commercial products</title><author>Wang, Mei ; Avula, Bharathi ; Wang, Yan-Hong ; Zhao, Jianping ; Avonto, Cristina ; Parcher, Jon F. ; Raman, Vijayasankar ; Zweigenbaum, Jerry A. ; Wylie, Philip L. ; Khan, Ikhlas A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c431t-5fb0632d0422f74d80fbeb7275a34a001ee217337c3e41c757257156d3c6fb523</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Biological and medical sciences</topic><topic>Chamaemelum nobile</topic><topic>Chamomile - chemistry</topic><topic>Chamomile - classification</topic><topic>Chemometric analysis</topic><topic>Chrysanthemum morifolium</topic><topic>Discriminant Analysis</topic><topic>Flowers - chemistry</topic><topic>Flowers - classification</topic><topic>Gas Chromatography-Mass Spectrometry - methods</topic><topic>General pharmacology</topic><topic>Matricaria chamomilla</topic><topic>Medical sciences</topic><topic>Oils, Volatile - chemistry</topic><topic>Pharmacognosy. Homeopathy. Health food</topic><topic>Pharmacology. Drug treatments</topic><topic>Plant Extracts - chemistry</topic><topic>Sample class prediction model</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Mei</creatorcontrib><creatorcontrib>Avula, Bharathi</creatorcontrib><creatorcontrib>Wang, Yan-Hong</creatorcontrib><creatorcontrib>Zhao, Jianping</creatorcontrib><creatorcontrib>Avonto, Cristina</creatorcontrib><creatorcontrib>Parcher, Jon F.</creatorcontrib><creatorcontrib>Raman, Vijayasankar</creatorcontrib><creatorcontrib>Zweigenbaum, Jerry A.</creatorcontrib><creatorcontrib>Wylie, Philip L.</creatorcontrib><creatorcontrib>Khan, Ikhlas A.</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Chemoreception Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><jtitle>Food chemistry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Mei</au><au>Avula, Bharathi</au><au>Wang, Yan-Hong</au><au>Zhao, Jianping</au><au>Avonto, Cristina</au><au>Parcher, Jon F.</au><au>Raman, Vijayasankar</au><au>Zweigenbaum, Jerry A.</au><au>Wylie, Philip L.</au><au>Khan, Ikhlas A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An integrated approach utilising chemometrics and GC/MS for classification of chamomile flowers, essential oils and commercial products</atitle><jtitle>Food chemistry</jtitle><addtitle>Food Chem</addtitle><date>2014-06-01</date><risdate>2014</risdate><volume>152</volume><spage>391</spage><epage>398</epage><pages>391-398</pages><issn>0308-8146</issn><eissn>1873-7072</eissn><coden>FOCHDJ</coden><abstract>•Three types of chamomile flowers, commercial products and oils were analysed.•A sample class prediction (SCP) model was constructed based on chemometrics.•Commercial products and oils containing chamomile were predicted by the SCP model.•Identification of markers correlated with different chamomiles was explored.
As part of an ongoing research program on authentication, safety and biological evaluation of phytochemicals and dietary supplements, an in-depth chemical investigation of different types of chamomile was performed. A collection of chamomile samples including authenticated plants, commercial products and essential oils was analysed by GC/MS. Twenty-seven authenticated plant samples representing three types of chamomile, viz. German chamomile, Roman chamomile and Juhua were analysed. This set of data was employed to construct a sample class prediction (SCP) model based on stepwise reduction of data dimensionality followed by principle component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The model was cross-validated with samples including authenticated plants and commercial products. The model demonstrated 100.0% accuracy for both recognition and prediction abilities. In addition, 35 commercial products and 11 essential oils purported to contain chamomile were subsequently predicted by the validated PLS-DA model. Furthermore, tentative identification of the marker compounds correlated with different types of chamomile was explored.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><pmid>24444953</pmid><doi>10.1016/j.foodchem.2013.11.118</doi><tpages>8</tpages></addata></record> |
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| ispartof | Food chemistry, 2014-06, Vol.152, p.391-398 |
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| subjects | Biological and medical sciences Chamaemelum nobile Chamomile - chemistry Chamomile - classification Chemometric analysis Chrysanthemum morifolium Discriminant Analysis Flowers - chemistry Flowers - classification Gas Chromatography-Mass Spectrometry - methods General pharmacology Matricaria chamomilla Medical sciences Oils, Volatile - chemistry Pharmacognosy. Homeopathy. Health food Pharmacology. Drug treatments Plant Extracts - chemistry Sample class prediction model |
| title | An integrated approach utilising chemometrics and GC/MS for classification of chamomile flowers, essential oils and commercial products |
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