期刊
VIBRATIONAL SPECTROSCOPY
卷 110, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.vibspec.2020.103149
关键词
Near-infrared; Ginseng; Geographical origin; Successive projection algorithm
资金
- National Natural Science Foundation of China [21375118, J1310041]
- Scientific Research Foundation of Sichuan Provincial Education Department of China [17TD0048]
- Scientific Research Foundation of Yibin University [2017ZD05]
- Sichuan Science and Technology Program of China [2018JY0504]
- Opening Fund of Key Lab of Process Analysis and Control of Sichuan Universities of China [2018005]
The feasibility of combining near-infrared (NIR) spectroscopy with chemometrics was explored to discriminate ginseng geographical origins. A total of 326 ginseng samples from three major ginseng producing regions were prepared and analyzed. After spectral pre-treatment, principal component analysis (PCA) was used for a preliminary analysis. Three algorithms, i.e., partial least squares-discriminant analysis (PLS-DA), soft independent modeling of class analogy classification (SIMCA) and successive projection algorithms-linear discriminant analysis (SPA-LDA), were applied to build models to discriminate origins of samples. The results showed that ginseng could be classified based on geographical origins with pattern recognition. By comparison, SPA-LDA is better than PLS-DA and SIMCA. It indicates that NIR spectroscopy combined with SPA-LDA is a potential and feasible tool for identifying ginseng according to geographical origin, but the effectiveness needs to be verified further.
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