Fluorescence spectral analysis for the discrimination of complex, similar mixtures with the aid of chemometrics.
An analytical method for the classification of complex real-world samples was researched and developed with the use of excitation-emission fluorescence matrix (EEFM) spectroscopy, using the medicinal herbs, Rhizoma corydalis decumbentis (RCD) and Rhizoma corydalis (RC) as example samples. The data set was obtained from various authentic RCD-A and RC-A, adulterated AD, and commercial RCD-C and RC-C samples. The spectra (range: λ(ex) = 215∼395 nm and λ(em) = 290∼560 nm), arranged in two- and three-way data matrix formats, were processed using principal component analysis (PCA) and parallel factor analysis (PARAFAC) to produce two-dimensional component-by-component plots for qualitative data classification. The RCD-A and RC-A object groups were clearly discriminated, but the AD and the RCD-C as well as RC-C samples were less well separated. PARAFAC analysis produced somewhat better discrimination, and loadings plots revealed the presence of the marker compound Protopine-a strongly fluorescing substance-as well as at least two other unidentified fluorescent components. Classification performance of the common K-nearest neighbors (KNN) and linear discrimination analysis (LDA) methods was relatively poor when compared with that of the back propagation- and radial basis function-artificial neural networks (BP-ANN and RBF-ANN) models on the basis of two- and three-way formatted data. The best results were obtained with the three-way fingerprints and the RBF-ANN model. Subsequently, the quality of the commercial samples (RCD-C and RC-C) was classified on the best optimized RBF-ANN model. Thus, EEFM spectroscopy, which provides three-way measured data, is potentially a powerful analytical technique for the analysis of complex real-world substances provided the classification is performed by the RBF-ANN or similar ANN methods.
State Key Laboratory of Food Science and Technology, Nanchang University, China. ynni@ncu.edu.cn
Yongnian
Y
Ni
Yanhua
Y
Lai
Serge
S
Kokot
D045424:Complex Mixtures / Q000032:analysis / Q000737:chemistry* / Q000145:classification; D031311:Corydalis / Q000737:chemistry; D008956:Models, Chemical; D016571:Neural Networks, Computer; D009930:Organic Chemicals / Q000032:analysis / Q000737:chemistry / Q000145:classification; D010936:Plant Extracts / Q000737:chemistry; D025341:Principal Component Analysis; D013050:Spectrometry, Fluorescence / Q000379:methods*
D045424:Complex Mixtures; D009930:Organic Chemicals; D010936:Plant Extracts