光谱学与光谱分析, 2010, 30 (11): 2954, 网络出版: 2011-01-26  

基于近红外光谱的人参与西洋参的快速鉴别研究

作者单位
1 中国农业大学食品科学与营养工程学院, 北京100083
2 许昌学院化学化工学院, 河南 许昌461000
3 Afexa Life Sciences Inc. Edmonton, T6N 1G1, Canada
摘要
基于近红外光谱分析技术结合模式判别方法建立了一种人参和西洋参鉴别的新方法。 收集根状、 根须和粉末状的样品共90份, 在有聚乙烯包装袋的情况下直接采集近红外光谱, 去除原始光谱中包装袋的显著吸收后进行了MSC与一阶导数处理, 然后采用移动窗口偏最小二乘法选择了建模光谱区间, 分别建立了PLS-DA, PCA-DA和SVM判别模型, 并对3种模型作了对比分析, 结果表明SVM判别效果最优, 其对预测集的正确判别率为100%。 该方法准确、 便捷, 可实际应用于企业原料药材的质量控制, 实现对原料药材的快速筛查<英文标题>Research on Fast Discrimination between Panax Ginseng and Panax Quinquefolium Based on Near Infrared Spectroscopy
Abstract
Near infrared spectroscopy combined with pattern recognition techniques were applied to develop a method of fast and nondestructive discrimination between Chinese ginseng and American ginseng. A total of 90 representative ginseng samples including root, fiber and powder were collected. NIR spectra of the samples were obtained directly with wrapped polyethylene packing film. MSC and first derivative were performed after the elimination of notable packing film absorbance in raw spectra. Then the informative wave bands were chosen by moving window partial least-squares regression method. PLS-DA, PCA-DA and SVM discrimination models were founded and their results were compared. SVM was proven to be the most effective method with 100% accurate identification rate for validation set. It indicates that the method founded is precise and convenient and can be practically used in practice for quality control and fast screening of raw herb materials.

黄亚伟, 王加华, 李晓云, Jacqueline J Shan, Lei Ling, 韩东海. 基于近红外光谱的人参与西洋参的快速鉴别研究[J]. 光谱学与光谱分析, 2010, 30(11): 2954. HUANG Ya-wei, WANG Jia-hua, LI Xiao-yun, Jacqueline J Shan, Lei Ling, HAN Dong-hai. [J]. Spectroscopy and Spectral Analysis, 2010, 30(11): 2954.

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