Classification of Tempranillo wines according to geographic origin: combination of mass spectrometry based electronic nose and chemometrics.

Rapid methods employing instruments such as electronic noses (EN) or gas sensors are used in the food and beverage industries to monitor and assess the composition and quality of products. Similar to other food industries, the wine industry has a clear need for simple, rapid and cost effective techniques for objectively evaluating the quality of grapes, wine and spirits. In this study a mass spectrometry based electronic nose (MS-EN) instrument combined with chemometrics was used to predict the geographical origin of Tempranillo wines produced in Australia and Spain. The MS-EN data generated were analyzed using principal components analysis (PCA), partial least squares discriminant analysis (PLS-DA) and stepwise linear discriminant analysis (SLDA) with full cross validation (leave-one-out method). The SLDA classified correctly 86% of the samples while PLS-DA 85% of Tempranillo wines according to their geographical origin. The relative benefits of using MS-EN will provide capability for rapid screening of wines. However, this technique does not provide the identification and quantitative determination of individual compounds responsible for the different aroma notes in the wine.

[1]  S. Buratti,et al.  Characterization and classification of Italian Barbera wines by using an electronic nose and an amperometric electronic tongue , 2004 .

[2]  B Dittmann,et al.  Strategies for the development of reliable QA/QC methods when working with mass spectrometry-based chemosensory systems , 2000 .

[3]  R T Marsili,et al.  SPME-MS-MVA as an electronic nose for the study of off-flavors in milk. , 1999, Journal of agricultural and food chemistry.

[4]  Ricard Boqué,et al.  Determination of ageing time of spirits in oak barrels using a headspace–mass spectrometry (HS-MS) electronic nose system and multivariate calibration , 2005, Analytical and bioanalytical chemistry.

[5]  G. Downey,et al.  Recent technological advances for the determination of food authenticity , 2006 .

[6]  Tormod Næs,et al.  A user-friendly guide to multivariate calibration and classification , 2002 .

[7]  H. Guth.  Quantitation and Sensory Studies of Character Impact Odorants of Different White Wine Varieties , 1997 .

[8]  Diana Hodgins,et al.  The electronic NOSE and its application to the manufacture of food products , 1995, The Journal of automatic chemistry.

[9]  Ioannis S. Arvanitoyannis,et al.  Application of quality control methods for assessing wine authenticity : Use of multivariate analysis (chemometrics) , 1999 .

[10]  U. Fischer,et al.  The impact of geographic origin, vintage and wine estate on sensory properties of Vitis vinifera cv. Riesling wines , 1999 .

[11]  Tom Fearn,et al.  Practical Nir Spectroscopy With Applications in Food and Beverage Analysis , 1993 .

[12]  M. Martí,et al.  Application of a headspace mass spectrometry system to the differentiation and classification of wines according to their origin, variety and ageing. , 2004, Journal of chromatography. A.

[13]  J. Gardner,et al.  Electronic noses and their application in the food industry , 1997 .

[14]  Christophe Cordella,et al.  Recent developments in food characterization and adulteration detection: technique-oriented perspectives. , 2002, Journal of agricultural and food chemistry.

[15]  C. Natale,et al.  Electronic nose systems to study shelf life and cultivar effect on tomato aroma profile , 2004 .

[16]  Richard G. Brereton,et al.  Chemometrics: Data Analysis for the Laboratory and Chemical Plant , 2003 .

[17]  M. Martí,et al.  Fast screening method for determining 2,4,6-trichloroanisole in wines using a headspace–mass spectrometry (HS–MS) system and multivariate calibration , 2003, Analytical and bioanalytical chemistry.

[18]  Daniel Cozzolino,et al.  Comparison of metal oxide-based electronic nose and mass spectrometry-based electronic nose for the prediction of red wine spoilage. , 2008, Journal of agricultural and food chemistry.

[19]  Daniel Cozzolino,et al.  Feasibility study on the use of a head space mass spectrometry electronic nose (MS e_nose) to monitor red wine spoilage induced by Brettanomyces yeast , 2007 .

[20]  M. Penza,et al.  Chemometric characterization of Italian wines by thin-film multisensors array and artificial neural networks , 2004 .

[21]  Michael Thompson,et al.  Applications of electronic noses and tongues in food analysis , 2004 .

[22]  V. Ferreira,et al.  Analysis of the aroma intensities of volatile compounds released from mild acid hydrolysates of odourless precursors extracted from Tempranillo and Grenache grapes using gas chromatography-olfactometry , 2004 .

[23]  João G Crespo,et al.  Monitoring the aroma production during wine-must fermentation with an electronic nose. , 2002, Biotechnology and bioengineering.

[24]  José Luis Pérez Pavón,et al.  Detection of adulterants in olive oil by headspace–mass spectrometry , 2002 .

[25]  Waldemar Wardencki,et al.  Aromagrams – Aromatic profiles in the appreciation of food quality , 2007 .

[26]  Daniel Cozzolino,et al.  Usefulness of chemometrics and mass spectrometry-based electronic nose to classify Australian white wines by their varietal origin. , 2005, Talanta.