Discrimination of adulterants in UHT milk samples by NIRS coupled with supervision discrimination techniques
A methodology was developed for distinguishing different ultra-high temperature (UHT) milk adulterants (water, urea, and formaldehyde) at various levels using NIR spectroscopy (NIRS) coupled with supervision discrimination techniques (SIMCA, SVM-DA, and PLS-DA). The figures of merit in discriminatio...
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Veröffentlicht in: | Analytical methods 2016-01, Vol.8 (39), p.724-728 |
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description | A methodology was developed for distinguishing different ultra-high temperature (UHT) milk adulterants (water, urea, and formaldehyde) at various levels using NIR spectroscopy (NIRS) coupled with supervision discrimination techniques (SIMCA, SVM-DA, and PLS-DA). The figures of merit in discrimination were established based on the results given by the best preprocessing for each technique. Discrimination of formaldehyde was 100% independent of the discrimination technique used. For water discrimination SVM-DA furnished better results as compared to PLS-DA and SIMCA. The same occurred with urea discrimination as well.
A methodology was developed for distinguishing different ultra-high temperature (UHT) milk adulterants (water, urea, and formaldehyde) at various levels using NIR spectroscopy (NIRS) coupled with supervision discrimination techniques (SIMCA, SVM-DA, and PLS-DA). |
doi_str_mv | 10.1039/c6ay01351a |
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A methodology was developed for distinguishing different ultra-high temperature (UHT) milk adulterants (water, urea, and formaldehyde) at various levels using NIR spectroscopy (NIRS) coupled with supervision discrimination techniques (SIMCA, SVM-DA, and PLS-DA).</description><identifier>ISSN: 1759-9660</identifier><identifier>EISSN: 1759-9679</identifier><identifier>DOI: 10.1039/c6ay01351a</identifier><language>eng</language><subject>Adulterants ; Discrimination ; Formaldehyde ; Mathematical analysis ; Milk ; Preprocessing ; UHT ; Ureas</subject><ispartof>Analytical methods, 2016-01, Vol.8 (39), p.724-728</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c323t-ccba539cb7a5564d5bf615ce5698f2eea78767cf9c8ea5c1ba1641461832f15d3</citedby><cites>FETCH-LOGICAL-c323t-ccba539cb7a5564d5bf615ce5698f2eea78767cf9c8ea5c1ba1641461832f15d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27915,27916</link.rule.ids></links><search><creatorcontrib>Luna, Aderval S</creatorcontrib><creatorcontrib>Pinho, Jéssica S. A</creatorcontrib><creatorcontrib>Machado, Luciana C</creatorcontrib><title>Discrimination of adulterants in UHT milk samples by NIRS coupled with supervision discrimination techniques</title><title>Analytical methods</title><description>A methodology was developed for distinguishing different ultra-high temperature (UHT) milk adulterants (water, urea, and formaldehyde) at various levels using NIR spectroscopy (NIRS) coupled with supervision discrimination techniques (SIMCA, SVM-DA, and PLS-DA). The figures of merit in discrimination were established based on the results given by the best preprocessing for each technique. Discrimination of formaldehyde was 100% independent of the discrimination technique used. For water discrimination SVM-DA furnished better results as compared to PLS-DA and SIMCA. The same occurred with urea discrimination as well.
A methodology was developed for distinguishing different ultra-high temperature (UHT) milk adulterants (water, urea, and formaldehyde) at various levels using NIR spectroscopy (NIRS) coupled with supervision discrimination techniques (SIMCA, SVM-DA, and PLS-DA).</description><subject>Adulterants</subject><subject>Discrimination</subject><subject>Formaldehyde</subject><subject>Mathematical analysis</subject><subject>Milk</subject><subject>Preprocessing</subject><subject>UHT</subject><subject>Ureas</subject><issn>1759-9660</issn><issn>1759-9679</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNpVkE1LAzEQhoMoWKsX70KOIqxmmk12cyz1o4WioO3B05LNJjS6XyZZZf-9WysVTzMDD--8PAidA7kGQsWN4rInQBnIAzSChIlI8EQc7ndOjtGJ92-EcEE5jFB5a71ytrK1DLapcWOwLLoyaCfr4LGt8Xq-wpUt37GXVVtqj_MePy6eX7BquuEu8JcNG-y7VrtP67cZxf_IoNWmth-d9qfoyMjS67PfOUbr-7vVbB4tnx4Ws-kyUnRCQ6RULhkVKk8kYzwuWG44MKUZF6mZaC2TNOGJMkKlWjIFuQQeQ8whpRMDrKBjdLnLbV2z_Ruyaqiky1LWuul8BmnMUgAS0wG92qHKNd47bbJ2qC5dnwHJtkqzGZ--_iidDvDFDnZe7bk_5fQbVIF1Wg</recordid><startdate>20160101</startdate><enddate>20160101</enddate><creator>Luna, Aderval S</creator><creator>Pinho, Jéssica S. A</creator><creator>Machado, Luciana C</creator><scope>AAYXX</scope><scope>CITATION</scope><scope>7SR</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope><scope>L7M</scope></search><sort><creationdate>20160101</creationdate><title>Discrimination of adulterants in UHT milk samples by NIRS coupled with supervision discrimination techniques</title><author>Luna, Aderval S ; Pinho, Jéssica S. A ; Machado, Luciana C</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c323t-ccba539cb7a5564d5bf615ce5698f2eea78767cf9c8ea5c1ba1641461832f15d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Adulterants</topic><topic>Discrimination</topic><topic>Formaldehyde</topic><topic>Mathematical analysis</topic><topic>Milk</topic><topic>Preprocessing</topic><topic>UHT</topic><topic>Ureas</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Luna, Aderval S</creatorcontrib><creatorcontrib>Pinho, Jéssica S. A</creatorcontrib><creatorcontrib>Machado, Luciana C</creatorcontrib><collection>CrossRef</collection><collection>Engineered Materials Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Analytical methods</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Luna, Aderval S</au><au>Pinho, Jéssica S. A</au><au>Machado, Luciana C</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Discrimination of adulterants in UHT milk samples by NIRS coupled with supervision discrimination techniques</atitle><jtitle>Analytical methods</jtitle><date>2016-01-01</date><risdate>2016</risdate><volume>8</volume><issue>39</issue><spage>724</spage><epage>728</epage><pages>724-728</pages><issn>1759-9660</issn><eissn>1759-9679</eissn><abstract>A methodology was developed for distinguishing different ultra-high temperature (UHT) milk adulterants (water, urea, and formaldehyde) at various levels using NIR spectroscopy (NIRS) coupled with supervision discrimination techniques (SIMCA, SVM-DA, and PLS-DA). The figures of merit in discrimination were established based on the results given by the best preprocessing for each technique. Discrimination of formaldehyde was 100% independent of the discrimination technique used. For water discrimination SVM-DA furnished better results as compared to PLS-DA and SIMCA. The same occurred with urea discrimination as well.
A methodology was developed for distinguishing different ultra-high temperature (UHT) milk adulterants (water, urea, and formaldehyde) at various levels using NIR spectroscopy (NIRS) coupled with supervision discrimination techniques (SIMCA, SVM-DA, and PLS-DA).</abstract><doi>10.1039/c6ay01351a</doi><tpages>5</tpages></addata></record> |
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source | Royal Society Of Chemistry Journals 2008-; Alma/SFX Local Collection |
subjects | Adulterants Discrimination Formaldehyde Mathematical analysis Milk Preprocessing UHT Ureas |
title | Discrimination of adulterants in UHT milk samples by NIRS coupled with supervision discrimination techniques |
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