Multivariate Analysis of 1H-NMR Spectra of Genetically Characterized Extra Virgin Olive Oils and Growth Soil Correlations
Mono-varietal extra virgin olive oils were micro-extracted from drupes that were selectively collected from 28 trees distributed in five different Southern Italian Apulian areas. Nuclear Magnetic Resonance (NMR) profiles of these oil samples were correlated to the genetic (young green material) and...
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| Veröffentlicht in: | Journal of the American Oil Chemists' Society 2011, Vol.88 (10), p.1463-1475 |
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| creator | Papadia, Paride Del Coco, Laura Muzzalupo, Innocenzo Rizzi, Marco Perri, Enzo Cesari, Gianluigi Simeone, Vito Mondelli, Donato Schena, Francesco P Fanizzi, Francesco P |
| description | Mono-varietal extra virgin olive oils were micro-extracted from drupes that were selectively collected from 28 trees distributed in five different Southern Italian Apulian areas. Nuclear Magnetic Resonance (NMR) profiles of these oil samples were correlated to the genetic (young green material) and soil (samples collected within the foliage projection) data of the tree of origin. Genetic analysis, performed on the samples using SSRs (Simple Sequence Repeats) by 9 microsatellite loci, confirmed the specific cultivar assignment (among Cima di Mola, Coratina, Ogliarola, and Oliva Rossa cultivars). Chemometric methods applied to 1H-NMR spectroscopic data were used for cultivar and geographical origin discrimination of the studied extra virgin olive oils. Linear Discriminant Analysis (LDA) afforded a high reliability degree for discriminating cultivars (almost 90% of prediction ability), and a good assigning ability for the geographical origin (Ogliarola and Coratina samples used as subsets). Soil analyses were performed for each tree. Regression analysis was applied to soil composition in order to correlate available nutrients and total metals with the content of fatty acids and minor components present in monovarietal extra virgin olive oils. In the case of oleic and linoleic fatty acids, and for some terpenes, B, Cr, Mn, Zn were found to give significant correlations. Zn and Mn were the most significant trace elements for all the correlations found (p |
| doi_str_mv | 10.1007/s11746-011-1812-1 |
| format | Article |
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Nuclear Magnetic Resonance (NMR) profiles of these oil samples were correlated to the genetic (young green material) and soil (samples collected within the foliage projection) data of the tree of origin. Genetic analysis, performed on the samples using SSRs (Simple Sequence Repeats) by 9 microsatellite loci, confirmed the specific cultivar assignment (among Cima di Mola, Coratina, Ogliarola, and Oliva Rossa cultivars). Chemometric methods applied to 1H-NMR spectroscopic data were used for cultivar and geographical origin discrimination of the studied extra virgin olive oils. Linear Discriminant Analysis (LDA) afforded a high reliability degree for discriminating cultivars (almost 90% of prediction ability), and a good assigning ability for the geographical origin (Ogliarola and Coratina samples used as subsets). Soil analyses were performed for each tree. Regression analysis was applied to soil composition in order to correlate available nutrients and total metals with the content of fatty acids and minor components present in monovarietal extra virgin olive oils. In the case of oleic and linoleic fatty acids, and for some terpenes, B, Cr, Mn, Zn were found to give significant correlations. Zn and Mn were the most significant trace elements for all the correlations found (p < 0.01). The results obtained (genetic, spectroscopic and soil analyses) are discussed as a multidisciplinary approach for setting up a strategy for a cultivar and/or geographic origin certification committed database construction.</description><identifier>ISSN: 0003-021X</identifier><identifier>EISSN: 1558-9331</identifier><identifier>DOI: 10.1007/s11746-011-1812-1</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer-Verlag</publisher><subject>Agriculture ; Biological and medical sciences ; Biomaterials ; Biotechnology ; certification ; Chemistry ; Chemistry and Materials Science ; chromium ; cultivars ; discriminant analysis ; Extra virgin olive oil ; Fat industries ; fatty acids ; Food industries ; Food origin characterization ; Food Science ; Fundamental and applied biological sciences. Psychology ; genetic techniques and protocols ; Industrial Chemistry/Chemical Engineering ; leaves ; manganese ; microsatellite repeats ; multivariate analysis ; NMR spectroscopy ; nuclear magnetic resonance spectroscopy ; nutrient availability ; Original Paper ; prediction ; provenance ; regression analysis ; soil ; Soil analysis ; Statistical analysis ; stone fruits ; terpenoids ; trees ; zinc</subject><ispartof>Journal of the American Oil Chemists' Society, 2011, Vol.88 (10), p.1463-1475</ispartof><rights>AOCS 2011</rights><rights>2011 American Oil Chemists' Society (AOCS)</rights><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-f255C-e2a78de4e5d3bc68921d9b06eaf2ffef55ed4ab3d8b57983b0d446ec508373d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11746-011-1812-1$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11746-011-1812-1$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,41464,42533,45550,45551,51294</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=24541518$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Papadia, Paride</creatorcontrib><creatorcontrib>Del Coco, Laura</creatorcontrib><creatorcontrib>Muzzalupo, Innocenzo</creatorcontrib><creatorcontrib>Rizzi, Marco</creatorcontrib><creatorcontrib>Perri, Enzo</creatorcontrib><creatorcontrib>Cesari, Gianluigi</creatorcontrib><creatorcontrib>Simeone, Vito</creatorcontrib><creatorcontrib>Mondelli, Donato</creatorcontrib><creatorcontrib>Schena, Francesco P</creatorcontrib><creatorcontrib>Fanizzi, Francesco P</creatorcontrib><title>Multivariate Analysis of 1H-NMR Spectra of Genetically Characterized Extra Virgin Olive Oils and Growth Soil Correlations</title><title>Journal of the American Oil Chemists' Society</title><addtitle>J Am Oil Chem Soc</addtitle><description>Mono-varietal extra virgin olive oils were micro-extracted from drupes that were selectively collected from 28 trees distributed in five different Southern Italian Apulian areas. Nuclear Magnetic Resonance (NMR) profiles of these oil samples were correlated to the genetic (young green material) and soil (samples collected within the foliage projection) data of the tree of origin. Genetic analysis, performed on the samples using SSRs (Simple Sequence Repeats) by 9 microsatellite loci, confirmed the specific cultivar assignment (among Cima di Mola, Coratina, Ogliarola, and Oliva Rossa cultivars). Chemometric methods applied to 1H-NMR spectroscopic data were used for cultivar and geographical origin discrimination of the studied extra virgin olive oils. Linear Discriminant Analysis (LDA) afforded a high reliability degree for discriminating cultivars (almost 90% of prediction ability), and a good assigning ability for the geographical origin (Ogliarola and Coratina samples used as subsets). Soil analyses were performed for each tree. Regression analysis was applied to soil composition in order to correlate available nutrients and total metals with the content of fatty acids and minor components present in monovarietal extra virgin olive oils. In the case of oleic and linoleic fatty acids, and for some terpenes, B, Cr, Mn, Zn were found to give significant correlations. Zn and Mn were the most significant trace elements for all the correlations found (p < 0.01). The results obtained (genetic, spectroscopic and soil analyses) are discussed as a multidisciplinary approach for setting up a strategy for a cultivar and/or geographic origin certification committed database construction.</description><subject>Agriculture</subject><subject>Biological and medical sciences</subject><subject>Biomaterials</subject><subject>Biotechnology</subject><subject>certification</subject><subject>Chemistry</subject><subject>Chemistry and Materials Science</subject><subject>chromium</subject><subject>cultivars</subject><subject>discriminant analysis</subject><subject>Extra virgin olive oil</subject><subject>Fat industries</subject><subject>fatty acids</subject><subject>Food industries</subject><subject>Food origin characterization</subject><subject>Food Science</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>genetic techniques and protocols</subject><subject>Industrial Chemistry/Chemical Engineering</subject><subject>leaves</subject><subject>manganese</subject><subject>microsatellite repeats</subject><subject>multivariate analysis</subject><subject>NMR spectroscopy</subject><subject>nuclear magnetic resonance spectroscopy</subject><subject>nutrient availability</subject><subject>Original Paper</subject><subject>prediction</subject><subject>provenance</subject><subject>regression analysis</subject><subject>soil</subject><subject>Soil analysis</subject><subject>Statistical analysis</subject><subject>stone fruits</subject><subject>terpenoids</subject><subject>trees</subject><subject>zinc</subject><issn>0003-021X</issn><issn>1558-9331</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><recordid>eNp9kc1u3CAUhVHVSp2meYCsyqZLWi4_Nl6OrHRSKclInTTKDmEDEyJqj8D5cZ--jFxl164QcD507gdCZ0C_AKX11wxQi4pQAAIKGIE3aAVSKtJwDm_RilLKCWVw9x59yPmhbBVncoXmq8c4hSeTgpkcXg8mzjlkPHoMF-T66gfeHVw_JXM82bjBTaE3Mc64vTfJ9JNL4bez-PzlGLkNaR8GvI3hyeFtiBmbweJNGp-ne7wbQ8TtmJKLZgrjkD-id97E7E7_rifo5tv5TXtBLreb7-36kngmZUscM7WyTjhpeddXqmFgm45WznjmvfNSOitMx63qZN0o3lErROV6WQasueUn6PPy7MHkUt0nM_Qh60MKv0yaNRNSgARVcmrJPYfo5td7oProVy9-dfGrj3416PW23UEF0BaULWgu1LB3ST-Mj6mozP_GC_RpgbwZtdmn0unnjlEQ5WsEq0Xz30SpTRv-B7_Nk2A</recordid><startdate>2011</startdate><enddate>2011</enddate><creator>Papadia, Paride</creator><creator>Del Coco, Laura</creator><creator>Muzzalupo, Innocenzo</creator><creator>Rizzi, Marco</creator><creator>Perri, Enzo</creator><creator>Cesari, Gianluigi</creator><creator>Simeone, Vito</creator><creator>Mondelli, Donato</creator><creator>Schena, Francesco P</creator><creator>Fanizzi, Francesco P</creator><general>Springer-Verlag</general><general>Springe-Verlag</general><general>Springer</general><scope>FBQ</scope><scope>IQODW</scope></search><sort><creationdate>2011</creationdate><title>Multivariate Analysis of 1H-NMR Spectra of Genetically Characterized Extra Virgin Olive Oils and Growth Soil Correlations</title><author>Papadia, Paride ; Del Coco, Laura ; Muzzalupo, Innocenzo ; Rizzi, Marco ; Perri, Enzo ; Cesari, Gianluigi ; Simeone, Vito ; Mondelli, Donato ; Schena, Francesco P ; Fanizzi, Francesco P</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-f255C-e2a78de4e5d3bc68921d9b06eaf2ffef55ed4ab3d8b57983b0d446ec508373d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Agriculture</topic><topic>Biological and medical sciences</topic><topic>Biomaterials</topic><topic>Biotechnology</topic><topic>certification</topic><topic>Chemistry</topic><topic>Chemistry and Materials Science</topic><topic>chromium</topic><topic>cultivars</topic><topic>discriminant analysis</topic><topic>Extra virgin olive oil</topic><topic>Fat industries</topic><topic>fatty acids</topic><topic>Food industries</topic><topic>Food origin characterization</topic><topic>Food Science</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>genetic techniques and protocols</topic><topic>Industrial Chemistry/Chemical Engineering</topic><topic>leaves</topic><topic>manganese</topic><topic>microsatellite repeats</topic><topic>multivariate analysis</topic><topic>NMR spectroscopy</topic><topic>nuclear magnetic resonance spectroscopy</topic><topic>nutrient availability</topic><topic>Original Paper</topic><topic>prediction</topic><topic>provenance</topic><topic>regression analysis</topic><topic>soil</topic><topic>Soil analysis</topic><topic>Statistical analysis</topic><topic>stone fruits</topic><topic>terpenoids</topic><topic>trees</topic><topic>zinc</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Papadia, Paride</creatorcontrib><creatorcontrib>Del Coco, Laura</creatorcontrib><creatorcontrib>Muzzalupo, Innocenzo</creatorcontrib><creatorcontrib>Rizzi, Marco</creatorcontrib><creatorcontrib>Perri, Enzo</creatorcontrib><creatorcontrib>Cesari, Gianluigi</creatorcontrib><creatorcontrib>Simeone, Vito</creatorcontrib><creatorcontrib>Mondelli, Donato</creatorcontrib><creatorcontrib>Schena, Francesco P</creatorcontrib><creatorcontrib>Fanizzi, Francesco P</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><jtitle>Journal of the American Oil Chemists' Society</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Papadia, Paride</au><au>Del Coco, Laura</au><au>Muzzalupo, Innocenzo</au><au>Rizzi, Marco</au><au>Perri, Enzo</au><au>Cesari, Gianluigi</au><au>Simeone, Vito</au><au>Mondelli, Donato</au><au>Schena, Francesco P</au><au>Fanizzi, Francesco P</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Multivariate Analysis of 1H-NMR Spectra of Genetically Characterized Extra Virgin Olive Oils and Growth Soil Correlations</atitle><jtitle>Journal of the American Oil Chemists' Society</jtitle><stitle>J Am Oil Chem Soc</stitle><date>2011</date><risdate>2011</risdate><volume>88</volume><issue>10</issue><spage>1463</spage><epage>1475</epage><pages>1463-1475</pages><issn>0003-021X</issn><eissn>1558-9331</eissn><abstract>Mono-varietal extra virgin olive oils were micro-extracted from drupes that were selectively collected from 28 trees distributed in five different Southern Italian Apulian areas. Nuclear Magnetic Resonance (NMR) profiles of these oil samples were correlated to the genetic (young green material) and soil (samples collected within the foliage projection) data of the tree of origin. Genetic analysis, performed on the samples using SSRs (Simple Sequence Repeats) by 9 microsatellite loci, confirmed the specific cultivar assignment (among Cima di Mola, Coratina, Ogliarola, and Oliva Rossa cultivars). Chemometric methods applied to 1H-NMR spectroscopic data were used for cultivar and geographical origin discrimination of the studied extra virgin olive oils. Linear Discriminant Analysis (LDA) afforded a high reliability degree for discriminating cultivars (almost 90% of prediction ability), and a good assigning ability for the geographical origin (Ogliarola and Coratina samples used as subsets). Soil analyses were performed for each tree. Regression analysis was applied to soil composition in order to correlate available nutrients and total metals with the content of fatty acids and minor components present in monovarietal extra virgin olive oils. In the case of oleic and linoleic fatty acids, and for some terpenes, B, Cr, Mn, Zn were found to give significant correlations. Zn and Mn were the most significant trace elements for all the correlations found (p < 0.01). The results obtained (genetic, spectroscopic and soil analyses) are discussed as a multidisciplinary approach for setting up a strategy for a cultivar and/or geographic origin certification committed database construction.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer-Verlag</pub><doi>10.1007/s11746-011-1812-1</doi><tpages>13</tpages></addata></record> |
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| subjects | Agriculture Biological and medical sciences Biomaterials Biotechnology certification Chemistry Chemistry and Materials Science chromium cultivars discriminant analysis Extra virgin olive oil Fat industries fatty acids Food industries Food origin characterization Food Science Fundamental and applied biological sciences. Psychology genetic techniques and protocols Industrial Chemistry/Chemical Engineering leaves manganese microsatellite repeats multivariate analysis NMR spectroscopy nuclear magnetic resonance spectroscopy nutrient availability Original Paper prediction provenance regression analysis soil Soil analysis Statistical analysis stone fruits terpenoids trees zinc |
| title | Multivariate Analysis of 1H-NMR Spectra of Genetically Characterized Extra Virgin Olive Oils and Growth Soil Correlations |
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