Multi-element Fingerprinting as a Tool in Origin Authentication of Four East China Marine Species
The contents of 25 elements in 4 types of commercial marine species from the East China Sea were determined by inductively coupled plasma mass spectrometry and atomic absorption spectrometry. The elemental composition was used to differentiate marine species according to geographical origin by multi...
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| Veröffentlicht in: | Journal of food science 2013-12, Vol.78 (12), p.C1852-C1857 |
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| container_title | Journal of food science |
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| creator | Guo, Lipan Gong, Like Yu, Yanlei Zhang, Hong |
| description | The contents of 25 elements in 4 types of commercial marine species from the East China Sea were determined by inductively coupled plasma mass spectrometry and atomic absorption spectrometry. The elemental composition was used to differentiate marine species according to geographical origin by multivariate statistical analysis. The results showed that principal component analysis could distinguish samples from different areas and reveal the elements which played the most important role in origin diversity. The established models by partial least squares discriminant analysis (PLS‐DA) and by probabilistic neural network (PNN) can both precisely predict the origin of the marine species. Further study indicated that PLS‐DA and PNN were efficacious in regional discrimination. The models from these 2 statistical methods, with an accuracy of 97.92% and 100%, respectively, could both distinguish samples from different areas without the need for species differentiation. |
| doi_str_mv | 10.1111/1750-3841.12302 |
| format | Article |
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The elemental composition was used to differentiate marine species according to geographical origin by multivariate statistical analysis. The results showed that principal component analysis could distinguish samples from different areas and reveal the elements which played the most important role in origin diversity. The established models by partial least squares discriminant analysis (PLS‐DA) and by probabilistic neural network (PNN) can both precisely predict the origin of the marine species. Further study indicated that PLS‐DA and PNN were efficacious in regional discrimination. The models from these 2 statistical methods, with an accuracy of 97.92% and 100%, respectively, could both distinguish samples from different areas without the need for species differentiation.</description><identifier>ISSN: 0022-1147</identifier><identifier>EISSN: 1750-3841</identifier><identifier>DOI: 10.1111/1750-3841.12302</identifier><identifier>PMID: 24261617</identifier><identifier>CODEN: JFDSAZ</identifier><language>eng</language><publisher>Hoboken, NJ: Blackwell Publishing Ltd</publisher><subject>Aquatic life ; Biological and medical sciences ; China ; Discriminant Analysis ; Food Analysis - methods ; Food industries ; Fundamental and applied biological sciences. Psychology ; ICP-MS ; Least-Squares Analysis ; Marine ; marine species ; Mass spectrometry ; multi-element fingerprinting ; Multivariate Analysis ; multivariate statistics ; Neural networks ; Origins ; Principal Component Analysis ; regional discrimination ; Reproducibility of Results ; Samples ; Seafood - analysis ; Statistical analysis ; Statistical methods ; Trace Elements - analysis</subject><ispartof>Journal of food science, 2013-12, Vol.78 (12), p.C1852-C1857</ispartof><rights>2013 Institute of Food Technologists</rights><rights>2015 INIST-CNRS</rights><rights>Copyright Institute of Food Technologists Dec 2013</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5062-8abf587dbd7fbccdda99b29e5f898f4b7e2866f196487c36db47c17e5469bc223</citedby><cites>FETCH-LOGICAL-c5062-8abf587dbd7fbccdda99b29e5f898f4b7e2866f196487c36db47c17e5469bc223</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2F1750-3841.12302$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2F1750-3841.12302$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28050124$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24261617$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Guo, Lipan</creatorcontrib><creatorcontrib>Gong, Like</creatorcontrib><creatorcontrib>Yu, Yanlei</creatorcontrib><creatorcontrib>Zhang, Hong</creatorcontrib><title>Multi-element Fingerprinting as a Tool in Origin Authentication of Four East China Marine Species</title><title>Journal of food science</title><addtitle>Journal of Food Science</addtitle><description>The contents of 25 elements in 4 types of commercial marine species from the East China Sea were determined by inductively coupled plasma mass spectrometry and atomic absorption spectrometry. The elemental composition was used to differentiate marine species according to geographical origin by multivariate statistical analysis. The results showed that principal component analysis could distinguish samples from different areas and reveal the elements which played the most important role in origin diversity. The established models by partial least squares discriminant analysis (PLS‐DA) and by probabilistic neural network (PNN) can both precisely predict the origin of the marine species. Further study indicated that PLS‐DA and PNN were efficacious in regional discrimination. The models from these 2 statistical methods, with an accuracy of 97.92% and 100%, respectively, could both distinguish samples from different areas without the need for species differentiation.</description><subject>Aquatic life</subject><subject>Biological and medical sciences</subject><subject>China</subject><subject>Discriminant Analysis</subject><subject>Food Analysis - methods</subject><subject>Food industries</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>ICP-MS</subject><subject>Least-Squares Analysis</subject><subject>Marine</subject><subject>marine species</subject><subject>Mass spectrometry</subject><subject>multi-element fingerprinting</subject><subject>Multivariate Analysis</subject><subject>multivariate statistics</subject><subject>Neural networks</subject><subject>Origins</subject><subject>Principal Component Analysis</subject><subject>regional discrimination</subject><subject>Reproducibility of Results</subject><subject>Samples</subject><subject>Seafood - analysis</subject><subject>Statistical analysis</subject><subject>Statistical methods</subject><subject>Trace Elements - analysis</subject><issn>0022-1147</issn><issn>1750-3841</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkUtv1DAUhS1ERYfCmh2yhJDYpLUdP5fVtBlAfYBaxNJyHKd1yThTOxHtv6_DTKcSm9YbP_Sd63vPAeADRvs4rwMsGCpKSfE-JiUir8Bs-_IazBAipMCYil3wNqUbNN1L_gbsEko45ljMgDkdu8EXrnNLFwZY-XDl4ir6MOQTNAkaeNn3HfQBnkd_lbfDcbjOqLdm8H2AfQurfozw2KQBzq99MPDUZL2DFytnvUvvwE5ruuTeb_Y98Ks6vpx_LU7OF9_mhyeFZYiTQpq6ZVI0dSPa2tqmMUrVRDnWSiVbWgtHJOctVpxKYUve1FRYLByjXNU2z7UHvqzrrmJ_O7o06KVP1nWdCa4fk8ZCoGwRYfJ5lCpa5rpYvQAVgjGJKc3op__Qm2xMyDNPFJISZfMzdbCmbOxTiq7V2e2lifcaIz1lqqcE9ZSg_pdpVnzc1B3rpWu2_GOIGfi8AUyypmujCdanJ04ihjCZGuRr7q_v3P1z_-rv1dHFYwfFWujT4O62QhP_aC5KwfTvs4Ve_PjJjqSqNCsfABwrxPQ</recordid><startdate>201312</startdate><enddate>201312</enddate><creator>Guo, Lipan</creator><creator>Gong, Like</creator><creator>Yu, Yanlei</creator><creator>Zhang, Hong</creator><general>Blackwell Publishing Ltd</general><general>Wiley</general><general>Wiley Subscription Services, Inc</general><scope>BSCLL</scope><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>7QO</scope><scope>7QR</scope><scope>7ST</scope><scope>7T7</scope><scope>7U7</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>P64</scope><scope>RC3</scope><scope>SOI</scope><scope>7X8</scope><scope>7TN</scope><scope>F1W</scope><scope>H95</scope><scope>L.G</scope></search><sort><creationdate>201312</creationdate><title>Multi-element Fingerprinting as a Tool in Origin Authentication of Four East China Marine Species</title><author>Guo, Lipan ; Gong, Like ; Yu, Yanlei ; Zhang, Hong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5062-8abf587dbd7fbccdda99b29e5f898f4b7e2866f196487c36db47c17e5469bc223</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Aquatic life</topic><topic>Biological and medical sciences</topic><topic>China</topic><topic>Discriminant Analysis</topic><topic>Food Analysis - methods</topic><topic>Food industries</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>ICP-MS</topic><topic>Least-Squares Analysis</topic><topic>Marine</topic><topic>marine species</topic><topic>Mass spectrometry</topic><topic>multi-element fingerprinting</topic><topic>Multivariate Analysis</topic><topic>multivariate statistics</topic><topic>Neural networks</topic><topic>Origins</topic><topic>Principal Component Analysis</topic><topic>regional discrimination</topic><topic>Reproducibility of Results</topic><topic>Samples</topic><topic>Seafood - analysis</topic><topic>Statistical analysis</topic><topic>Statistical methods</topic><topic>Trace Elements - analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Guo, Lipan</creatorcontrib><creatorcontrib>Gong, Like</creatorcontrib><creatorcontrib>Yu, Yanlei</creatorcontrib><creatorcontrib>Zhang, Hong</creatorcontrib><collection>Istex</collection><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>Biotechnology Research Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Environment Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Toxicology Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>Environment Abstracts</collection><collection>MEDLINE - Academic</collection><collection>Oceanic Abstracts</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>Journal of food science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Guo, Lipan</au><au>Gong, Like</au><au>Yu, Yanlei</au><au>Zhang, Hong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Multi-element Fingerprinting as a Tool in Origin Authentication of Four East China Marine Species</atitle><jtitle>Journal of food science</jtitle><addtitle>Journal of Food Science</addtitle><date>2013-12</date><risdate>2013</risdate><volume>78</volume><issue>12</issue><spage>C1852</spage><epage>C1857</epage><pages>C1852-C1857</pages><issn>0022-1147</issn><eissn>1750-3841</eissn><coden>JFDSAZ</coden><abstract>The contents of 25 elements in 4 types of commercial marine species from the East China Sea were determined by inductively coupled plasma mass spectrometry and atomic absorption spectrometry. 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| subjects | Aquatic life Biological and medical sciences China Discriminant Analysis Food Analysis - methods Food industries Fundamental and applied biological sciences. Psychology ICP-MS Least-Squares Analysis Marine marine species Mass spectrometry multi-element fingerprinting Multivariate Analysis multivariate statistics Neural networks Origins Principal Component Analysis regional discrimination Reproducibility of Results Samples Seafood - analysis Statistical analysis Statistical methods Trace Elements - analysis |
| title | Multi-element Fingerprinting as a Tool in Origin Authentication of Four East China Marine Species |
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