Can spectroscopy geographically classify Sauvignon Blanc wines from Australia and New Zealand

The combination of UV, visible (Vis), near-infrared (NIR) and mid-infrared (MIR) spectroscopy with multivariate data analysis was explored as a tool to classify commercial Sauvignon Blanc (Vitis vinifera L., var. Sauvignon Blanc) wines from Australia and New Zealand. Wines (n = 64) were analysed in transmission using UV, Vis, NIR and MIR regions of the electromagnetic spectrum. Principal component analysis (PCA), soft independent modelling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA) were used to classify Sauvignon Blanc wines according to their geographical origin using full cross validation (leave-one-out) as a validation method. Overall PLS-DA models correctly classified 86% of the wines from New Zealand and 73%, 86% and 93% of the Australian wines using NIR, MIR and the concatenation of NIR and MIR, respectively. Misclassified Australian wines were those sourced from the Adelaide Hills of South Australia. These results demonstrate the potential of combining spectroscopy with chemometrics data analysis techniques as a rapid method to classify Sauvignon Blanc wines according to their geographical origin.

[1]  M. J. García,et al.  Geographical differentiation of white wines from three subzones of the designation of origin Valencia , 2003 .

[2]  Robert G. Dambergs,et al.  Preliminary study on the application of visible–near infrared spectroscopy and chemometrics to classify Riesling wines from different countries , 2008 .

[3]  S. Kuznesof,et al.  Policy initiatives for regional foods: some insights from consumer research , 1998 .

[4]  R. Skaggs,et al.  Product‐country images and international food marketing: Relationships and research needs , 1996 .

[5]  Simon D. Kelly,et al.  Tracing the geographical origin of food: The application of multi-element and multi-isotope analysis , 2005 .

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

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

[8]  Wine judging, context and New Zealand Sauvignon Blanc Évaluation de vins, contexte et Sauvignon Blanc Néo-Zélandais , 2006 .

[9]  S. Ruth,et al.  An overview of analytical methods for determining the geographical origin of food products , 2008 .

[10]  Gerard Downey,et al.  Food and food ingredient authentication by mid-infrared spectroscopy and chemometrics , 1998 .

[11]  G. G. Dull,et al.  Near Infrared Spectrophotometric Determination of Individual Sugars in Aqueous Mixtures , 1986 .

[12]  Norbert Jakubowski,et al.  Classification of German white wines with certified brand of origin by multielement quantitation and pattern recognition techniques. , 2004, Journal of agricultural and food chemistry.

[13]  Miguel Ángel Gómez-Nieto,et al.  Ultraviolet-visible spectroscopy and pattern recognition methods for differentiation and classification of wines , 2006 .

[14]  K. Geoffrey White,et al.  The distinctive flavour of New Zealand Sauvignon blanc: Sensory characterisation by wine professionals , 2007 .

[15]  Koert van Ittersum,et al.  The Role of the Region of Origin and EU Certificates of Origin in Consumer Evaluation of Food Products , 2001 .

[16]  G. Mead.  Microbiological Hazards from Red Meat and Their Control , 1994 .

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

[18]  Matthias Otto,et al.  Chemometrics: Statistics and Computer Application in Analytical Chemistry , 1999 .

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

[20]  I. S. Pretorius,et al.  The influence of yeast on the aroma of Sauvignon Blanc wine. , 2009, Food microbiology.

[21]  Robert G. Dambergs,et al.  Mid infrared spectroscopy and multivariate analysis: a tool to discriminate between organic and non-organic wines grown in Australia , 2009 .

[22]  K. Héberger,et al.  Supervised pattern recognition in food analysis. , 2007, Journal of chromatography. A.

[23]  B. Lendl,et al.  Rapid method for the discrimination of red wine cultivars based on mid-infrared spectroscopy of phenolic wine extracts. , 2001, Journal of agricultural and food chemistry.

[24]  J. Boulet,et al.  A Fourier transform infrared spectroscopy study of wine polysaccharides , 2007 .

[25]  Daniel Cozzolino,et al.  Development of a rapid "fingerprinting" system for wine authenticity by mid-infrared spectroscopy. , 2006, Journal of agricultural and food chemistry.

[26]  Daniel Cozzolino,et al.  Geographical origin of Sauvignon Blanc wines predicted by mass spectrometry and metal oxide based electronic nose. , 2009, Analytica chimica acta.