Use of direct headspace-mass spectrometry coupled with chemometrics to predict aroma properties in Australian Riesling wine
Identifieur interne :
002D56 ( PascalFrancis/Curation );
précédent :
002D55;
suivant :
002D57
Use of direct headspace-mass spectrometry coupled with chemometrics to predict aroma properties in Australian Riesling wine
Auteurs : Daniel Cozzolino [
Australie] ;
Heather E. Smyth [
Australie] ;
Wies Cynkar [
Australie] ;
Les Janik [
Australie] ;
Robert G. Dambergs [
Australie] ;
Mark Gishen [
Australie]
Source :
-
Analytica chimica acta [ 0003-2670 ] ; 2008.
RBID : Pascal:08-0457556
Descripteurs français
- Pascal (Inist)
- Espace tête,
Spectrométrie masse,
Chimiométrie,
Arôme,
Vin,
Détecteur de gaz,
Nez électronique,
Odeur,
Appareillage,
Analyse composante principale,
Régression PLS,
Etalonnage,
Coefficient corrélation,
Erreur quadratique moyenne,
Parfum,
Pomme,
Fruit,
Miel,
Analyse quantitative,
Riesling,
Capteur chimique,
Australie.
- Wicri :
English descriptors
- KwdEn :
- Apple,
Aroma,
Australia,
Calibration,
Chemical sensor,
Chemometrics,
Correlation coefficient,
Electronic nose,
Fruit,
Gas detector,
Headspace,
Honey,
Instrumentation,
Mass spectrometry,
Mean square error,
Odor,
PLS regression,
Perfume,
Principal component analysis,
Quantitative analysis,
Riesling,
Wine.
Abstract
The aim of this study was to investigate the potential use of a direct headspace-mass spectrometry electronic nose instrument (MS e-nose) combined with chemometrics as rapid, objective and low cost technique to measure aroma properties in Australian Riesling wines. Commercial bottled Riesling wines were analyzed using a MS e-nose instrument and by a sensory panel. The MS e-nose data generated were analyzed using principal components analysis (PCA) and partial least squares (PLS1) regression using full cross validation (leave one out method). Calibration models between MS e-nose data and aroma properties were developed using partial least squares (PLS1) regression, yielding coefficients of correlation in calibration (R) and root mean square error of cross validation of 0.75 (RMSECV: 0.85) for estery, 0.89 (RMSECV: 0.94) for perfume floral, 0.82 (RMSECV: 0.62) for lemon, 0.82 (RMSECV: 0.32) for stewed apple, 0.67 (RMSECV: 0.99) for passion fruit and 0.90 (RMSECV: 0.86) for honey, respectively. The relative benefits of using MS e-nose will provide capability for rapid screening of wines before sensory analysis. However, the basic deficiency of this technique is lack of possible identification and quantitative determination of individual compounds responsible for the different aroma notes in the wine.
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| A09 | 01 | 1 | ENG | @1 5th Symposium In Vivo Analytica Scientia. Melbourne, Australia, 22-25 July 2007 |
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| A14 | 01 | | | @1 The Australian Wine Research Institute, Waite Road, Urrbrae, P.O. Box 197 @2 Adelaide, SA 5064 @3 AUS @Z 1 aut. @Z 3 aut. @Z 4 aut. @Z 5 aut. @Z 6 aut. |
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| A14 | 02 | | | @1 School of Agriculture and Wine, Faculty of Sciences, The University of Adelaide, Waite Campus @2 Glen Osmond, SA 5064 @3 AUS @Z 2 aut. |
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| A15 | 01 | | | @1 Consulting to the Wine Industry @2 Northcote, Vic. 3070 @3 AUS @Z 1 aut. |
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| A15 | 02 | | | @1 Laboraboire de Chimie Analytique, AgroParisTech @2 75005 Paris @3 FRA @Z 2 aut. |
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| C01 | 01 | | ENG | @0 The aim of this study was to investigate the potential use of a direct headspace-mass spectrometry electronic nose instrument (MS e-nose) combined with chemometrics as rapid, objective and low cost technique to measure aroma properties in Australian Riesling wines. Commercial bottled Riesling wines were analyzed using a MS e-nose instrument and by a sensory panel. The MS e-nose data generated were analyzed using principal components analysis (PCA) and partial least squares (PLS1) regression using full cross validation (leave one out method). Calibration models between MS e-nose data and aroma properties were developed using partial least squares (PLS1) regression, yielding coefficients of correlation in calibration (R) and root mean square error of cross validation of 0.75 (RMSECV: 0.85) for estery, 0.89 (RMSECV: 0.94) for perfume floral, 0.82 (RMSECV: 0.62) for lemon, 0.82 (RMSECV: 0.32) for stewed apple, 0.67 (RMSECV: 0.99) for passion fruit and 0.90 (RMSECV: 0.86) for honey, respectively. The relative benefits of using MS e-nose will provide capability for rapid screening of wines before sensory analysis. However, the basic deficiency of this technique is lack of possible identification and quantitative determination of individual compounds responsible for the different aroma notes in the wine. |
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| pR |
| A30 | 01 | 1 | ENG | @1 In Vino Analytica Scientia Symposium @2 5 @3 Melbourne AUS @4 2007-07-22 |
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|
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Le document en format XML
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</affiliation><author><name sortKey="Cynkar, Wies" sort="Cynkar, Wies" uniqKey="Cynkar W" first="Wies" last="Cynkar">Wies Cynkar</name>
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</affiliation><series><title level="j" type="main">Analytica chimica acta</title>
<title level="j" type="abbreviated">Anal. chim. acta</title>
<idno type="ISSN">0003-2670</idno>
<imprint><date when="2008">2008</date>
</imprint><seriesStmt><title level="j" type="main">Analytica chimica acta</title>
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</seriesStmt><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Apple</term>
<term>Aroma</term>
<term>Australia</term>
<term>Calibration</term>
<term>Chemical sensor</term>
<term>Chemometrics</term>
<term>Correlation coefficient</term>
<term>Electronic nose</term>
<term>Fruit</term>
<term>Gas detector</term>
<term>Headspace</term>
<term>Honey</term>
<term>Instrumentation</term>
<term>Mass spectrometry</term>
<term>Mean square error</term>
<term>Odor</term>
<term>PLS regression</term>
<term>Perfume</term>
<term>Principal component analysis</term>
<term>Quantitative analysis</term>
<term>Riesling</term>
<term>Wine</term>
</keywords><keywords scheme="Pascal" xml:lang="fr"><term>Espace tête</term>
<term>Spectrométrie masse</term>
<term>Chimiométrie</term>
<term>Arôme</term>
<term>Vin</term>
<term>Détecteur de gaz</term>
<term>Nez électronique</term>
<term>Odeur</term>
<term>Appareillage</term>
<term>Analyse composante principale</term>
<term>Régression PLS</term>
<term>Etalonnage</term>
<term>Coefficient corrélation</term>
<term>Erreur quadratique moyenne</term>
<term>Parfum</term>
<term>Pomme</term>
<term>Fruit</term>
<term>Miel</term>
<term>Analyse quantitative</term>
<term>Riesling</term>
<term>Capteur chimique</term>
<term>Australie</term>
</keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>Australie</term>
</keywords><keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Vin</term>
<term>Fruit</term>
<term>Miel</term>
<term>Analyse quantitative</term>
</keywords><front><div type="abstract" xml:lang="en">The aim of this study was to investigate the potential use of a direct headspace-mass spectrometry electronic nose instrument (MS e-nose) combined with chemometrics as rapid, objective and low cost technique to measure aroma properties in Australian Riesling wines. Commercial bottled Riesling wines were analyzed using a MS e-nose instrument and by a sensory panel. The MS e-nose data generated were analyzed using principal components analysis (PCA) and partial least squares (PLS1) regression using full cross validation (leave one out method). Calibration models between MS e-nose data and aroma properties were developed using partial least squares (PLS1) regression, yielding coefficients of correlation in calibration (R) and root mean square error of cross validation of 0.75 (RMSECV: 0.85) for estery, 0.89 (RMSECV: 0.94) for perfume floral, 0.82 (RMSECV: 0.62) for lemon, 0.82 (RMSECV: 0.32) for stewed apple, 0.67 (RMSECV: 0.99) for passion fruit and 0.90 (RMSECV: 0.86) for honey, respectively. The relative benefits of using MS e-nose will provide capability for rapid screening of wines before sensory analysis. However, the basic deficiency of this technique is lack of possible identification and quantitative determination of individual compounds responsible for the different aroma notes in the wine.</div>
</front><inist><standard h6="B"><pA><fA01 i1="01" i2="1"><s0>0003-2670</s0>
</fA01><fA02 i1="01"><s0>ACACAM</s0>
</fA02><fA03 i2="1"><s0>Anal. chim. acta</s0>
</fA03><fA05><s2>621</s2>
</fA05><fA08 i1="01" i2="1" l="ENG"><s1>Use of direct headspace-mass spectrometry coupled with chemometrics to predict aroma properties in Australian Riesling wine</s1>
</fA08><fA09 i1="01" i2="1" l="ENG"><s1>5th Symposium In Vivo Analytica Scientia. Melbourne, Australia, 22-25 July 2007</s1>
</fA09><fA11 i1="01" i2="1"><s1>COZZOLINO (Daniel)</s1>
</fA11><fA11 i1="02" i2="1"><s1>SMYTH (Heather E.)</s1>
</fA11><fA11 i1="03" i2="1"><s1>CYNKAR (Wies)</s1>
</fA11><fA11 i1="04" i2="1"><s1>JANIK (Les)</s1>
</fA11><fA11 i1="05" i2="1"><s1>DAMBERGS (Robert G.)</s1>
</fA11><fA11 i1="06" i2="1"><s1>GISHEN (Mark)</s1>
</fA11><fA12 i1="01" i2="1"><s1>SCOLLARY (Geoffrey)</s1>
<s9>ed.</s9>
</fA12><fA12 i1="02" i2="1"><s1>RUTLEDGE (Douglas N.)</s1>
<s9>ed.</s9>
</fA12><fA12 i1="03" i2="1"><s1>TOWNSHEND (Alan)</s1>
<s9>ed.</s9>
</fA12><fA14 i1="01"><s1>The Australian Wine Research Institute, Waite Road, Urrbrae, P.O. Box 197</s1>
<s2>Adelaide, SA 5064</s2>
<s3>AUS</s3>
<sZ>1 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
<sZ>6 aut.</sZ>
</fA14><fA14 i1="02"><s1>School of Agriculture and Wine, Faculty of Sciences, The University of Adelaide, Waite Campus</s1>
<s2>Glen Osmond, SA 5064</s2>
<s3>AUS</s3>
<sZ>2 aut.</sZ>
</fA14><fA15 i1="01"><s1>Consulting to the Wine Industry</s1>
<s2>Northcote, Vic. 3070</s2>
<s3>AUS</s3>
<sZ>1 aut.</sZ>
</fA15><fA15 i1="02"><s1>Laboraboire de Chimie Analytique, AgroParisTech</s1>
<s2>75005 Paris</s2>
<s3>FRA</s3>
<sZ>2 aut.</sZ>
</fA15><fA15 i1="03"><s1>School of Chemistry, The University</s1>
<s2>Hull HU6 7RX</s2>
<s3>GBR</s3>
<sZ>3 aut.</sZ>
</fA15><fA20><s1>2-7</s1>
</fA20><fA21><s1>2008</s1>
</fA21><fA23 i1="01"><s0>ENG</s0>
</fA23><fA43 i1="01"><s1>INIST</s1>
<s2>3950</s2>
<s5>354000197611220010</s5>
</fA43><fA44><s0>0000</s0>
<s1>© 2008 INIST-CNRS. All rights reserved.</s1>
</fA44><fA45><s0>31 ref.</s0>
</fA45><fA47 i1="01" i2="1"><s0>08-0457556</s0>
</fA47><fA60><s1>P</s1>
<s2>C</s2>
</fA60><fA64 i1="01" i2="1"><s0>Analytica chimica acta</s0>
</fA64><fA66 i1="01"><s0>NLD</s0>
</fA66><fC01 i1="01" l="ENG"><s0>The aim of this study was to investigate the potential use of a direct headspace-mass spectrometry electronic nose instrument (MS e-nose) combined with chemometrics as rapid, objective and low cost technique to measure aroma properties in Australian Riesling wines. Commercial bottled Riesling wines were analyzed using a MS e-nose instrument and by a sensory panel. The MS e-nose data generated were analyzed using principal components analysis (PCA) and partial least squares (PLS1) regression using full cross validation (leave one out method). Calibration models between MS e-nose data and aroma properties were developed using partial least squares (PLS1) regression, yielding coefficients of correlation in calibration (R) and root mean square error of cross validation of 0.75 (RMSECV: 0.85) for estery, 0.89 (RMSECV: 0.94) for perfume floral, 0.82 (RMSECV: 0.62) for lemon, 0.82 (RMSECV: 0.32) for stewed apple, 0.67 (RMSECV: 0.99) for passion fruit and 0.90 (RMSECV: 0.86) for honey, respectively. The relative benefits of using MS e-nose will provide capability for rapid screening of wines before sensory analysis. However, the basic deficiency of this technique is lack of possible identification and quantitative determination of individual compounds responsible for the different aroma notes in the wine.</s0>
</fC01><fC02 i1="01" i2="X"><s0>001C04C</s0>
</fC02><fC02 i1="02" i2="X"><s0>001C04A</s0>
</fC02><fC03 i1="01" i2="X" l="FRE"><s0>Espace tête</s0>
<s5>01</s5>
</fC03><fC03 i1="01" i2="X" l="ENG"><s0>Headspace</s0>
<s5>01</s5>
</fC03><fC03 i1="01" i2="X" l="SPA"><s0>Espacio cabeza</s0>
<s5>01</s5>
</fC03><fC03 i1="02" i2="X" l="FRE"><s0>Spectrométrie masse</s0>
<s5>02</s5>
</fC03><fC03 i1="02" i2="X" l="ENG"><s0>Mass spectrometry</s0>
<s5>02</s5>
</fC03><fC03 i1="02" i2="X" l="SPA"><s0>Espectrometría masa</s0>
<s5>02</s5>
</fC03><fC03 i1="03" i2="X" l="FRE"><s0>Chimiométrie</s0>
<s5>03</s5>
</fC03><fC03 i1="03" i2="X" l="ENG"><s0>Chemometrics</s0>
<s5>03</s5>
</fC03><fC03 i1="03" i2="X" l="SPA"><s0>Quimiometría</s0>
<s5>03</s5>
</fC03><fC03 i1="04" i2="X" l="FRE"><s0>Arôme</s0>
<s5>04</s5>
</fC03><fC03 i1="04" i2="X" l="ENG"><s0>Aroma</s0>
<s5>04</s5>
</fC03><fC03 i1="04" i2="X" l="SPA"><s0>Aroma</s0>
<s5>04</s5>
</fC03><fC03 i1="05" i2="X" l="FRE"><s0>Vin</s0>
<s1>SUB</s1>
<s5>05</s5>
</fC03><fC03 i1="05" i2="X" l="ENG"><s0>Wine</s0>
<s1>SUB</s1>
<s5>05</s5>
</fC03><fC03 i1="05" i2="X" l="SPA"><s0>Vino</s0>
<s1>SUB</s1>
<s5>05</s5>
</fC03><fC03 i1="06" i2="X" l="FRE"><s0>Détecteur de gaz</s0>
<s5>06</s5>
</fC03><fC03 i1="06" i2="X" l="ENG"><s0>Gas detector</s0>
<s5>06</s5>
</fC03><fC03 i1="06" i2="X" l="SPA"><s0>Detector de gas</s0>
<s5>06</s5>
</fC03><fC03 i1="07" i2="X" l="FRE"><s0>Nez électronique</s0>
<s5>07</s5>
</fC03><fC03 i1="07" i2="X" l="ENG"><s0>Electronic nose</s0>
<s5>07</s5>
</fC03><fC03 i1="07" i2="X" l="SPA"><s0>Nariz electrónica</s0>
<s5>07</s5>
</fC03><fC03 i1="08" i2="X" l="FRE"><s0>Odeur</s0>
<s5>08</s5>
</fC03><fC03 i1="08" i2="X" l="ENG"><s0>Odor</s0>
<s5>08</s5>
</fC03><fC03 i1="08" i2="X" l="SPA"><s0>Olor</s0>
<s5>08</s5>
</fC03><fC03 i1="09" i2="X" l="FRE"><s0>Appareillage</s0>
<s5>09</s5>
</fC03><fC03 i1="09" i2="X" l="ENG"><s0>Instrumentation</s0>
<s5>09</s5>
</fC03><fC03 i1="09" i2="X" l="SPA"><s0>Instrumentación</s0>
<s5>09</s5>
</fC03><fC03 i1="10" i2="X" l="FRE"><s0>Analyse composante principale</s0>
<s5>10</s5>
</fC03><fC03 i1="10" i2="X" l="ENG"><s0>Principal component analysis</s0>
<s5>10</s5>
</fC03><fC03 i1="10" i2="X" l="SPA"><s0>Análisis componente principal</s0>
<s5>10</s5>
</fC03><fC03 i1="11" i2="X" l="FRE"><s0>Régression PLS</s0>
<s5>11</s5>
</fC03><fC03 i1="11" i2="X" l="ENG"><s0>PLS regression</s0>
<s5>11</s5>
</fC03><fC03 i1="11" i2="X" l="SPA"><s0>Regresión PLS</s0>
<s5>11</s5>
</fC03><fC03 i1="12" i2="X" l="FRE"><s0>Etalonnage</s0>
<s5>12</s5>
</fC03><fC03 i1="12" i2="X" l="ENG"><s0>Calibration</s0>
<s5>12</s5>
</fC03><fC03 i1="12" i2="X" l="SPA"><s0>Contraste</s0>
<s5>12</s5>
</fC03><fC03 i1="13" i2="X" l="FRE"><s0>Coefficient corrélation</s0>
<s5>13</s5>
</fC03><fC03 i1="13" i2="X" l="ENG"><s0>Correlation coefficient</s0>
<s5>13</s5>
</fC03><fC03 i1="13" i2="X" l="SPA"><s0>Coeficiente correlación</s0>
<s5>13</s5>
</fC03><fC03 i1="14" i2="X" l="FRE"><s0>Erreur quadratique moyenne</s0>
<s5>14</s5>
</fC03><fC03 i1="14" i2="X" l="ENG"><s0>Mean square error</s0>
<s5>14</s5>
</fC03><fC03 i1="14" i2="X" l="SPA"><s0>Error medio cuadrático</s0>
<s5>14</s5>
</fC03><fC03 i1="15" i2="X" l="FRE"><s0>Parfum</s0>
<s5>15</s5>
</fC03><fC03 i1="15" i2="X" l="ENG"><s0>Perfume</s0>
<s5>15</s5>
</fC03><fC03 i1="15" i2="X" l="SPA"><s0>Perfume</s0>
<s5>15</s5>
</fC03><fC03 i1="16" i2="X" l="FRE"><s0>Pomme</s0>
<s5>16</s5>
</fC03><fC03 i1="16" i2="X" l="ENG"><s0>Apple</s0>
<s5>16</s5>
</fC03><fC03 i1="16" i2="X" l="SPA"><s0>Manzana</s0>
<s5>16</s5>
</fC03><fC03 i1="17" i2="X" l="FRE"><s0>Fruit</s0>
<s5>17</s5>
</fC03><fC03 i1="17" i2="X" l="ENG"><s0>Fruit</s0>
<s5>17</s5>
</fC03><fC03 i1="17" i2="X" l="SPA"><s0>Fruto</s0>
<s5>17</s5>
</fC03><fC03 i1="18" i2="X" l="FRE"><s0>Miel</s0>
<s5>18</s5>
</fC03><fC03 i1="18" i2="X" l="ENG"><s0>Honey</s0>
<s5>18</s5>
</fC03><fC03 i1="18" i2="X" l="SPA"><s0>Miel</s0>
<s5>18</s5>
</fC03><fC03 i1="19" i2="X" l="FRE"><s0>Analyse quantitative</s0>
<s5>19</s5>
</fC03><fC03 i1="19" i2="X" l="ENG"><s0>Quantitative analysis</s0>
<s5>19</s5>
</fC03><fC03 i1="19" i2="X" l="SPA"><s0>Análisis cuantitativo</s0>
<s5>19</s5>
</fC03><fC03 i1="20" i2="X" l="FRE"><s0>Riesling</s0>
<s5>22</s5>
</fC03><fC03 i1="20" i2="X" l="ENG"><s0>Riesling</s0>
<s5>22</s5>
</fC03><fC03 i1="20" i2="X" l="SPA"><s0>Vino riesling</s0>
<s5>22</s5>
</fC03><fC03 i1="21" i2="X" l="FRE"><s0>Capteur chimique</s0>
<s5>35</s5>
</fC03><fC03 i1="21" i2="X" l="ENG"><s0>Chemical sensor</s0>
<s5>35</s5>
</fC03><fC03 i1="21" i2="X" l="SPA"><s0>Captador químico</s0>
<s5>35</s5>
</fC03><fC03 i1="22" i2="X" l="FRE"><s0>Australie</s0>
<s2>NG</s2>
<s5>41</s5>
</fC03><fC03 i1="22" i2="X" l="ENG"><s0>Australia</s0>
<s2>NG</s2>
<s5>41</s5>
</fC03><fC03 i1="22" i2="X" l="SPA"><s0>Australia</s0>
<s2>NG</s2>
<s5>41</s5>
</fC03><fC07 i1="01" i2="X" l="FRE"><s0>Océanie</s0>
<s2>NG</s2>
</fC07><fC07 i1="01" i2="X" l="ENG"><s0>Oceania</s0>
<s2>NG</s2>
</fC07><fC07 i1="01" i2="X" l="SPA"><s0>Oceania</s0>
<s2>NG</s2>
</fC07><fN21><s1>294</s1>
</fN21><pR><fA30 i1="01" i2="1" l="ENG"><s1>In Vino Analytica Scientia Symposium</s1>
<s2>5</s2>
<s3>Melbourne AUS</s3>
<s4>2007-07-22</s4>
</fA30>
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