Fingerprint Approaches Coupled with Chemometrics to Discriminate Geographic Origin of Imported Salmon in China's Consumer Market
Of the salmon sold in China's consumer market, 92% was labelled as Norwegian salmon, but was in fact was mainly imported from Chile. The aim of this study was to establish an effective method for discriminating the geographic origin of imported salmon using two fingerprint approaches, Near-infr...
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| creator | Fu, Xianshu Hong, Xuezhen Liao, Jinyan Ji, Qingge Li, Chaofeng Zhang, Mingzhou Ye, Zihong Yu, Xiaoping |
| description | Of the salmon sold in China's consumer market, 92% was labelled as Norwegian salmon, but was in fact was mainly imported from Chile. The aim of this study was to establish an effective method for discriminating the geographic origin of imported salmon using two fingerprint approaches, Near-infrared (NIR) spectroscopy and mineral element fingerprint (MEF). In total, 80 salmon (40 from Norway and 40 from Chile) were tested, and data generated by NIR and MEF were analysed via various chemometrics. Four spectral preprocessing methods, including vector normalization (VN), Savitzky Golay (SG) smoothing, first derivative (FD) and second derivative (SD), were employed on the raw NIR data, and a partial least squares (PLS) model based on the FD + SG9 pretreatment could successfully differentiate Norwegian salmons from Chilean salmons, with a R
value of 98.5%. Analysis of variance (ANOVA) and multiple comparative analysis were employed on the contents of 16 mineral elements including Pb, Fe, Cu, Zn, Al, Sr, Ni, As, Cr, V, Se, Mn, K, Ca, Na and Mg. The results showed that Fe, Zn, Al, Ni, As, Cr, V, Se, Ca and Na could be used as characteristic elements to discriminate the geographical origin of the imported salmon, and the discrimination rate of the linear discriminant analysis (LDA) model, trained on the above 10 elements, could reach up to 98.8%. The results demonstrate that both NIR and MEF could be effective tools for the rapid discrimination of geographic origin of imported salmon in China's consumer market. |
| doi_str_mv | 10.3390/foods10122986 |
| format | Article |
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value of 98.5%. Analysis of variance (ANOVA) and multiple comparative analysis were employed on the contents of 16 mineral elements including Pb, Fe, Cu, Zn, Al, Sr, Ni, As, Cr, V, Se, Mn, K, Ca, Na and Mg. The results showed that Fe, Zn, Al, Ni, As, Cr, V, Se, Ca and Na could be used as characteristic elements to discriminate the geographical origin of the imported salmon, and the discrimination rate of the linear discriminant analysis (LDA) model, trained on the above 10 elements, could reach up to 98.8%. The results demonstrate that both NIR and MEF could be effective tools for the rapid discrimination of geographic origin of imported salmon in China's consumer market.</description><identifier>ISSN: 2304-8158</identifier><identifier>EISSN: 2304-8158</identifier><identifier>DOI: 10.3390/foods10122986</identifier><identifier>PMID: 34945538</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Abdomen ; Accuracy ; Aluminum ; Aquaculture ; Calcium ; Chemometrics ; Chromium ; Comparative analysis ; Copper ; data preprocessing ; Discriminant analysis ; Fatty acids ; Fingerprints ; Food science ; Geography ; Iron ; Manganese ; mineral element fingerprint (MEF) ; Near infrared radiation ; near-infrared (NIR) ; Nickel ; Noise ; partial least squares (PLS) ; principal component analysis (PCA) ; Salmon ; Scientific imaging ; Seafood ; Selenium ; Variance analysis ; Zinc</subject><ispartof>Foods, 2021-12, Vol.10 (12), p.2986</ispartof><rights>2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 by the authors. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c481t-b4994e61dc52133539ef5a6176e9314121513d788abaacbfe5368646de8bea33</citedby><cites>FETCH-LOGICAL-c481t-b4994e61dc52133539ef5a6176e9314121513d788abaacbfe5368646de8bea33</cites><orcidid>0000-0002-8203-8090 ; 0000-0001-7107-9586</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8701728/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8701728/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34945538$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Fu, Xianshu</creatorcontrib><creatorcontrib>Hong, Xuezhen</creatorcontrib><creatorcontrib>Liao, Jinyan</creatorcontrib><creatorcontrib>Ji, Qingge</creatorcontrib><creatorcontrib>Li, Chaofeng</creatorcontrib><creatorcontrib>Zhang, Mingzhou</creatorcontrib><creatorcontrib>Ye, Zihong</creatorcontrib><creatorcontrib>Yu, Xiaoping</creatorcontrib><title>Fingerprint Approaches Coupled with Chemometrics to Discriminate Geographic Origin of Imported Salmon in China's Consumer Market</title><title>Foods</title><addtitle>Foods</addtitle><description>Of the salmon sold in China's consumer market, 92% was labelled as Norwegian salmon, but was in fact was mainly imported from Chile. The aim of this study was to establish an effective method for discriminating the geographic origin of imported salmon using two fingerprint approaches, Near-infrared (NIR) spectroscopy and mineral element fingerprint (MEF). In total, 80 salmon (40 from Norway and 40 from Chile) were tested, and data generated by NIR and MEF were analysed via various chemometrics. Four spectral preprocessing methods, including vector normalization (VN), Savitzky Golay (SG) smoothing, first derivative (FD) and second derivative (SD), were employed on the raw NIR data, and a partial least squares (PLS) model based on the FD + SG9 pretreatment could successfully differentiate Norwegian salmons from Chilean salmons, with a R
value of 98.5%. Analysis of variance (ANOVA) and multiple comparative analysis were employed on the contents of 16 mineral elements including Pb, Fe, Cu, Zn, Al, Sr, Ni, As, Cr, V, Se, Mn, K, Ca, Na and Mg. The results showed that Fe, Zn, Al, Ni, As, Cr, V, Se, Ca and Na could be used as characteristic elements to discriminate the geographical origin of the imported salmon, and the discrimination rate of the linear discriminant analysis (LDA) model, trained on the above 10 elements, could reach up to 98.8%. The results demonstrate that both NIR and MEF could be effective tools for the rapid discrimination of geographic origin of imported salmon in China's consumer market.</description><subject>Abdomen</subject><subject>Accuracy</subject><subject>Aluminum</subject><subject>Aquaculture</subject><subject>Calcium</subject><subject>Chemometrics</subject><subject>Chromium</subject><subject>Comparative analysis</subject><subject>Copper</subject><subject>data preprocessing</subject><subject>Discriminant analysis</subject><subject>Fatty acids</subject><subject>Fingerprints</subject><subject>Food science</subject><subject>Geography</subject><subject>Iron</subject><subject>Manganese</subject><subject>mineral element fingerprint (MEF)</subject><subject>Near infrared radiation</subject><subject>near-infrared (NIR)</subject><subject>Nickel</subject><subject>Noise</subject><subject>partial least squares (PLS)</subject><subject>principal component analysis (PCA)</subject><subject>Salmon</subject><subject>Scientific imaging</subject><subject>Seafood</subject><subject>Selenium</subject><subject>Variance analysis</subject><subject>Zinc</subject><issn>2304-8158</issn><issn>2304-8158</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>DOA</sourceid><recordid>eNpdkr9v1TAQgCMEolXpyIosMcASiH8l9oJUhbY8qagD3S3HuSR-JHGwHRAbf3odXqn68GLr_PnT3fmy7DUuPlAqi4-dc23ABSZEivJZdkpowXKBuXj-5HySnYewL9KSmApKXmYnlEnGORWn2Z8rO_fgF2_niC6WxTttBgiodusyQot-2TigeoDJTRC9NQFFhz7bYLyd7KwjoGtwvdfLYA269ba3M3Id2k2L8zG9_6bHyc0oResh8e828xzWCTz6qv13iK-yF50eA5w_7GfZ3dXlXf0lv7m93tUXN7lhAse8YVIyKHFrOMGUciqh47rEVQmSYoYJ5pi2lRC60do0HXBaipKVLYgGNKVn2e6gbZ3eq1TupP1v5bRVfwPO90r7aM0ISrISY6gkTg7WdbypOt2AbLUmIDBsrk8H17I2E7QG5uj1eCQ9vpntoHr3U4mqwBURSfD-QeDdjxVCVFPqKIyjnsGtQZESM8K3H0vo2__QvVv9nDq1UaSqSi6rROUHyngXgofuMRlcqG1S1NGkJP7N0woe6X9zQe8B7vG71Q</recordid><startdate>20211203</startdate><enddate>20211203</enddate><creator>Fu, Xianshu</creator><creator>Hong, Xuezhen</creator><creator>Liao, Jinyan</creator><creator>Ji, Qingge</creator><creator>Li, Chaofeng</creator><creator>Zhang, Mingzhou</creator><creator>Ye, Zihong</creator><creator>Yu, Xiaoping</creator><general>MDPI AG</general><general>MDPI</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QR</scope><scope>7T7</scope><scope>7X2</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>HCIFZ</scope><scope>M0K</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-8203-8090</orcidid><orcidid>https://orcid.org/0000-0001-7107-9586</orcidid></search><sort><creationdate>20211203</creationdate><title>Fingerprint Approaches Coupled with Chemometrics to Discriminate Geographic Origin of Imported Salmon in China's Consumer Market</title><author>Fu, Xianshu ; Hong, Xuezhen ; Liao, Jinyan ; Ji, Qingge ; Li, Chaofeng ; Zhang, Mingzhou ; Ye, Zihong ; Yu, Xiaoping</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c481t-b4994e61dc52133539ef5a6176e9314121513d788abaacbfe5368646de8bea33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Abdomen</topic><topic>Accuracy</topic><topic>Aluminum</topic><topic>Aquaculture</topic><topic>Calcium</topic><topic>Chemometrics</topic><topic>Chromium</topic><topic>Comparative analysis</topic><topic>Copper</topic><topic>data preprocessing</topic><topic>Discriminant analysis</topic><topic>Fatty acids</topic><topic>Fingerprints</topic><topic>Food science</topic><topic>Geography</topic><topic>Iron</topic><topic>Manganese</topic><topic>mineral element fingerprint (MEF)</topic><topic>Near infrared radiation</topic><topic>near-infrared (NIR)</topic><topic>Nickel</topic><topic>Noise</topic><topic>partial least squares (PLS)</topic><topic>principal component analysis (PCA)</topic><topic>Salmon</topic><topic>Scientific imaging</topic><topic>Seafood</topic><topic>Selenium</topic><topic>Variance analysis</topic><topic>Zinc</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Fu, Xianshu</creatorcontrib><creatorcontrib>Hong, Xuezhen</creatorcontrib><creatorcontrib>Liao, Jinyan</creatorcontrib><creatorcontrib>Ji, Qingge</creatorcontrib><creatorcontrib>Li, Chaofeng</creatorcontrib><creatorcontrib>Zhang, Mingzhou</creatorcontrib><creatorcontrib>Ye, Zihong</creatorcontrib><creatorcontrib>Yu, Xiaoping</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Chemoreception Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Agricultural Science Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>SciTech Premium Collection</collection><collection>Agricultural Science Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Foods</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fu, Xianshu</au><au>Hong, Xuezhen</au><au>Liao, Jinyan</au><au>Ji, Qingge</au><au>Li, Chaofeng</au><au>Zhang, Mingzhou</au><au>Ye, Zihong</au><au>Yu, Xiaoping</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fingerprint Approaches Coupled with Chemometrics to Discriminate Geographic Origin of Imported Salmon in China's Consumer Market</atitle><jtitle>Foods</jtitle><addtitle>Foods</addtitle><date>2021-12-03</date><risdate>2021</risdate><volume>10</volume><issue>12</issue><spage>2986</spage><pages>2986-</pages><issn>2304-8158</issn><eissn>2304-8158</eissn><abstract>Of the salmon sold in China's consumer market, 92% was labelled as Norwegian salmon, but was in fact was mainly imported from Chile. The aim of this study was to establish an effective method for discriminating the geographic origin of imported salmon using two fingerprint approaches, Near-infrared (NIR) spectroscopy and mineral element fingerprint (MEF). In total, 80 salmon (40 from Norway and 40 from Chile) were tested, and data generated by NIR and MEF were analysed via various chemometrics. Four spectral preprocessing methods, including vector normalization (VN), Savitzky Golay (SG) smoothing, first derivative (FD) and second derivative (SD), were employed on the raw NIR data, and a partial least squares (PLS) model based on the FD + SG9 pretreatment could successfully differentiate Norwegian salmons from Chilean salmons, with a R
value of 98.5%. Analysis of variance (ANOVA) and multiple comparative analysis were employed on the contents of 16 mineral elements including Pb, Fe, Cu, Zn, Al, Sr, Ni, As, Cr, V, Se, Mn, K, Ca, Na and Mg. The results showed that Fe, Zn, Al, Ni, As, Cr, V, Se, Ca and Na could be used as characteristic elements to discriminate the geographical origin of the imported salmon, and the discrimination rate of the linear discriminant analysis (LDA) model, trained on the above 10 elements, could reach up to 98.8%. The results demonstrate that both NIR and MEF could be effective tools for the rapid discrimination of geographic origin of imported salmon in China's consumer market.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>34945538</pmid><doi>10.3390/foods10122986</doi><orcidid>https://orcid.org/0000-0002-8203-8090</orcidid><orcidid>https://orcid.org/0000-0001-7107-9586</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Abdomen Accuracy Aluminum Aquaculture Calcium Chemometrics Chromium Comparative analysis Copper data preprocessing Discriminant analysis Fatty acids Fingerprints Food science Geography Iron Manganese mineral element fingerprint (MEF) Near infrared radiation near-infrared (NIR) Nickel Noise partial least squares (PLS) principal component analysis (PCA) Salmon Scientific imaging Seafood Selenium Variance analysis Zinc |
| title | Fingerprint Approaches Coupled with Chemometrics to Discriminate Geographic Origin of Imported Salmon in China's Consumer Market |
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