Discrimination of industrial products by on-line near infrared spectroscopy with an improved dendrogram

Near infrared (NIR) spectroscopy technique has shown great power and gained wide acceptance for analyzing complicated samples. The present work is to distinguish different brands of tobacco products by using on-line NIR spectroscopy and pattern recognition techniques. Moreover, since each brand contains a large number of samples, an improved dendrogram was proposed to show the classification of different brands. The results suggest that NIR spectroscopy combined with principal component analysis (PCA) and hierarchical cluster analysis (HCA) performs well in discrimination of the different brands, and the improved dendrogram could provide more information about the difference of the brands.