Use of direct headspace-mass spectrometry coupled with chemometrics to predict aroma properties in Australian Riesling wine

Cozzolino, Daniel, Smyth, Heather E., Cynkar, Wies, Janik, Les, Dambergs, Robert G. and Gishen, Mark (2008). Use of direct headspace-mass spectrometry coupled with chemometrics to predict aroma properties in Australian Riesling wine. In: Geoffrey Scollary, Douglas N. Rutledge and Alan Townshend, Papers presented at the 5th Symposium In Vino Analytica Scientia - In Vino 2007. 5th Symposium In Vino Analytica Scientia (In Vino 2007), Melbourne, Australia, (2-7). 22-25 July 2007. doi:10.1016/j.aca.2007.09.036


Author Cozzolino, Daniel
Smyth, Heather E.
Cynkar, Wies
Janik, Les
Dambergs, Robert G.
Gishen, Mark
Title of paper Use of direct headspace-mass spectrometry coupled with chemometrics to predict aroma properties in Australian Riesling wine
Conference name 5th Symposium In Vino Analytica Scientia (In Vino 2007)
Conference location Melbourne, Australia
Conference dates 22-25 July 2007
Proceedings title Papers presented at the 5th Symposium In Vino Analytica Scientia - In Vino 2007   Check publisher's open access policy
Journal name Analytica Chimica Acta   Check publisher's open access policy
Place of Publication Amsterdam, Netherlands
Publisher Elsevier BV
Publication Year 2008
Year available 2007
Sub-type Fully published paper
DOI 10.1016/j.aca.2007.09.036
ISSN 0003-2670
1873-4324
Editor Geoffrey Scollary
Douglas N. Rutledge
Alan Townshend
Volume 621
Issue 1
Start page 2
End page 7
Total pages 5
Language eng
Formatted Abstract/Summary
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.
Keyword Headspace mass spectrometry
Electronic nose
Riesling
Australia
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status Non-UQ
Additional Notes Available online 22 September 2007

Document type: Conference Paper
Collection: Queensland Alliance for Agriculture and Food Innovation
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 15 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 19 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Mon, 07 Mar 2011, 15:25:11 EST