| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1234449 | Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy | 2012 | 6 Pages |
A new assay of identifying wines was developed based on fingerprints of three-dimensional fluorescence spectra, and 30 samples from different manufacturers were analyzed. The techniques of principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used to differentiate and evaluate the character parameters of wines’ three-dimensional fluorescence spectra. At the same time, the back-propagation network (BPN) was applied to predict the attribution of unknown samples. The results of PCA and HCA showed that there was definite different information among the wine samples from different manufacturers. It was promising that the method could be applied to distinguish wine samples produced by different manufacturers. The proposed method could provide the criterion for the quality control of wines.
Graphical abstractFigure optionsDownload full-size imageDownload as PowerPoint slideHighlights► Three-dimensional fluorescence fingerprints were established to distinguish wine samples. ► A pattern recognition approach could identify wine samples from different manufacturers. ► The proposed method could provide the criterion for the quality control of wines.
