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

Discrimination of industrial products by on-line near infrared spectroscopy with an improved dendrogram
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通过改进的树状图的在线近红外光谱法鉴别工业产品

DOI:
10.1016/j.cclet.2011.04.019
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发表时间:
2011-10
影响因子:
9.1
通讯作者:
Shao, Xue Guang
Shao, Xue Guang
中科院分区:
化学1区
文献类型:
--
作者:
Liu, Jing Jing;Xu, Heng;Cai, Wen Sheng;Shao, Xue Guang

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近红外光谱技术在分析复杂样品中显示出强大的功能,并得到广泛的认可。本论文的工作是利用在线近红外光谱技术和模式识别技术来区分不同品牌的烟草制品。此外,由于每个品牌包含大量的样本,提出了一种改进的树状图来显示不同品牌的分类。结果表明,近红外光谱法结合主成分分析(PCA)和层次聚类分析(HCA)可以有效区分不同品牌,改进后的树状图可以提供更多的品牌差异信息。
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.
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