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Study on Rapid Identification of Medicinal Plants of Paris Polyphylla from Different Origin Areas by NIR spectroscopy

文献类型： 外文期刊

作者： Zhao Yan-li 1 ; Zhang Ji 1 ; Yuan Tian-jun 2 ; Shen Tao 3 ; Hou Ying 2 ; Yang Shi-hua 2 ; Li Wei 2 ; Wang Yuan-zhong 1 ; Jin 1 ;

作者机构： 1.Yunnan Acad Agr Sci, Inst Med Plants, Kunming 650200, Peoples R China

2.Yunnan Reascend Tobacco Technol Grp Co Ltd, Kunming 650106, Peoples R China

3.Yuxi Normal Univ, Coll Resources & Environm, Yuxi 653100, Peoples R China

关键词： Paris polyphylla;NIR spectroscopy;Principal component analysis-mahalanobis distance;Partial least square discrimination analysis;Spectrum range selection

期刊名称：SPECTROSCOPY AND SPECTRAL ANALYSIS （ 影响因子：0.589； 五年影响因子：0.504 ）

ISSN： 1000-0593

年卷期： 2014 年 34 卷 7 期

页码：

收录情况： SCI

摘要： Based on near infrared spectroscopy, seventy samples of wild medicinal plants of Paris polyphylla from Guizhou, Guangxi and Yunnan Provinces were collected to identify their geographical origins. Multiplication signal correction (MSC), standard normal variate (SNV), first derivative (FD), second derivative (SD), savitzky-Golay filter (SG), and Norris derivative filter (ND) were conducted to optimize the original spectra of fifty samples of training set. The results showed that the method MSC combined with SD and ND presented the best results of spectra pretreatment. According to spectrum standard deviation, spectrum range (7 450 similar to 4 050 cm(-1)) was chosen and principal component analysis-mahalanobis distance (PCA-MD) method was used to build the model. Its first three principal components, i. e. cumulative contribution, determination coefficient (R-2), root-mean-square error of calibration (RMSEC) and root-mean-square error of prediction (RMSEP) were 89. 44%, 97. 58%, 0. 179 6 and 0. 266 4, respectively, and the prediction accuracy is 90%. Furthermore, according to variable importance plot (VIP), spectrum range (7 135. 33 similar to 4 007. 35 cm(-1)) was chosen and partial least square discrimination analysis (PLS-DA) was applied to establish the model. Its first three principal components cumulative contribution, R-2, RMSEC and RMSEP were 89. 28%, 95. 88%, 0.234 8 and 0.348 2, respectively, and the prediction accuracy is 100%. Comparing the two methods, we found that spectrum range chosen by VIP and model built by PLS-DA could provide greater accuracy in identifying paris polyphylla from different origin areas. The method supplied foundation for authenticity and quality evaluation of traditional Chinese medicine.

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[1]Study on Application of NIR Spectral Information Screening in Identification of Maca Origin. Wang Yuan-zhong,Zhao Yan-li,Zhang Ji,Jin Hang. 2016

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