引用本文:
Jing Jing Liu, Heng Xu, Wen Sheng Cai, Xue Guang Shao. Discrimination of industrial products by on-line near infrared spectroscopy with an improved dendrogram[J]. Chinese Chemical Letters,
2011, 22(10): 1241-1244.
doi:
10.1016/j.cclet.2011.04.019
Citation: Jing Jing Liu, Heng Xu, Wen Sheng Cai, Xue Guang Shao. Discrimination of industrial products by on-line near infrared spectroscopy with an improved dendrogram[J]. Chinese Chemical Letters, 2011, 22(10): 1241-1244. doi: 10.1016/j.cclet.2011.04.019
Citation: Jing Jing Liu, Heng Xu, Wen Sheng Cai, Xue Guang Shao. Discrimination of industrial products by on-line near infrared spectroscopy with an improved dendrogram[J]. Chinese Chemical Letters, 2011, 22(10): 1241-1244. doi: 10.1016/j.cclet.2011.04.019
Discrimination of industrial products by on-line near infrared spectroscopy with an improved dendrogram
摘要:
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 MR 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.
English
Discrimination of industrial products by on-line near infrared spectroscopy with an improved dendrogram
Abstract:
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 MR 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.
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