The determination of wine authenticity and the detection of adulteration are attracting an increasing amount of attention for wine producers, researchers and consumers. Wine authentication and classification based on geographical origin has been widely studied. Most of these studies have achieved successful classification results. However, these studies have involved complicated and expensive procedures. Visible and near infrared spectroscopy (Vis-NIR) is recognized as a rapid and non-destructive technique. In recent years, several studies have been conducted using Vis-NIR spectroscopy to analyze wine for both quantitative and qualitative purposes. The aim of this research was to investigate the geographical classification of wines using Vis-NIR spectroscopy. The effect of temperature and measurement mode (transmission and transflectance) on Vis-NIR spectra was investigated to identify optimal conditions for wine sample analysis. It was found the optimal temperature is between 30 to 35°C and the shorter pathlength measurement condition has better prediction ability. Classification by geographical origin using Vis-NIR spectroscopy was investigated for sixty-three Tempranillo wines from Spain and Australia, and fifty Riesling wines from Australia, New Zealand and Europe. Discriminant partial least square regression (DPLS) and linear discriminant analysis (LDA) based on PCA scores were used to perform classification. Over 90% of the Tempranillo wines were correctly classified according to their geographical region using both DPLS and LDA. A classification rate of 72% was achieved for the Riesling wines. Vis-NIR technique provides a similar degree of reliability on wine classification comparable to those obtained using chemical composition. The results of this study demonstrate potential for Vis-NIR spectroscopy combined with multivariate analysis as a rapid method for classifying wines by geographical origin. / Thesis (M.Eng.Sc.)--School of Chemical Engineering, 2006.
| Identifer | oai:union.ndltd.org:ADTP/263887 |
| Date | January 2006 |
| Creators | Liu, Liang |
| Source Sets | Australiasian Digital Theses Program |
| Language | en_US |
| Detected Language | English |
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