Authenticity identification and classification of Rhodiola species in traditional Tibetan medicine based on Fourier transform near-infrared spectroscopy and chemometrics analysis.
Spectrochimica Acta Part A: Molecular & Biomolecular Spectroscopy
Short Title:
Spectrochimica Acta Part A: Molecular & Biomolecular Spectroscopy
Format:
Journal Article
Publication Date:
2018/11/05/
Pages:
131 - 140
Sources ID:
93476
Notes:
Accession Number: 131031583; Li, Tao 1; Email Address: scdxlitao@scu.edu.cn Su, Chen 1; Affiliation: 1: Department of Natural Medicine, West China School of Pharmacy, Sichuan University, and Key Laboratory of Drug Targeting, Ministry of Education, No. 17, Section 3, Ren-Min-Nan-Lu Road, Chengdu, Sichuan 610041, PR China; Source Info: Nov2018, Vol. 204, p131; Subject Term: BANDPASS filters; Subject Term: COMPOSITE materials; Subject Term: ROSEROOT; Subject Term: FOURIER transform infrared spectroscopy; Subject Term: FASCIOLA hepatica; Author-Supplied Keyword: Authenticity identification; Author-Supplied Keyword: Chemometrics; Author-Supplied Keyword: Fourier transform near-infrared spectroscopy; Author-Supplied Keyword: Kernel extreme learning machine (KELM); Author-Supplied Keyword: Partial least squares discriminant analysis (PLS-DA); Author-Supplied Keyword: Rhodiola; Number of Pages: 10p; Document Type: ArticleAccession Number: 131031583; Li, Tao 1; Email Address: scdxlitao@scu.edu.cn Su, Chen 1; Affiliation: 1: Department of Natural Medicine, West China School of Pharmacy, Sichuan University, and Key Laboratory of Drug Targeting, Ministry of Education, No. 17, Section 3, Ren-Min-Nan-Lu Road, Chengdu, Sichuan 610041, PR China; Source Info: Nov2018, Vol. 204, p131; Subject Term: BANDPASS filters; Subject Term: COMPOSITE materials; Subject Term: ROSEROOT; Subject Term: FOURIER transform infrared spectroscopy; Subject Term: FASCIOLA hepatica; Author-Supplied Keyword: Authenticity identification; Author-Supplied Keyword: Chemometrics; Author-Supplied Keyword: Fourier transform near-infrared spectroscopy; Author-Supplied Keyword: Kernel extreme learning machine (KELM); Author-Supplied Keyword: Partial least squares discriminant analysis (PLS-DA); Author-Supplied Keyword: Rhodiola; Number of Pages: 10p; Document Type: ArticleAccession Number: 131031583; Li, Tao 1; Email Address: scdxlitao@scu.edu.cn Su, Chen 1; Affiliation: 1: Department of Natural Medicine, West China School of Pharmacy, Sichuan University, and Key Laboratory of Drug Targeting, Ministry of Education, No. 17, Section 3, Ren-Min-Nan-Lu Road, Chengdu, Sichuan 610041, PR China; Source Info: Nov2018, Vol. 204, p131; Subject Term: BANDPASS filters; Subject Term: COMPOSITE materials; Subject Term: ROSEROOT; Subject Term: FOURIER transform infrared spectroscopy; Subject Term: FASCIOLA hepatica; Author-Supplied Keyword: Authenticity identification; Author-Supplied Keyword: Chemometrics; Author-Supplied Keyword: Fourier transform near-infrared spectroscopy; Author-Supplied Keyword: Kernel extreme learning machine (KELM); Author-Supplied Keyword: Partial least squares discriminant analysis (PLS-DA); Author-Supplied Keyword: Rhodiola; Number of Pages: 10p; Document Type: Article
Collection:
Himalayan and Tibetan Medicine
Visibility:
Public (group default)
Abstract:
(Show)
Rhodiola is an increasingly widely used traditional Tibetan medicine and traditional Chinese medicine in China. The composition profiles of bioactive compounds are somewhat jagged according to different species, which makes it crucial to identify authentic Rhodiola species accurately so as to ensure clinical application of Rhodiola . In this paper, a nondestructive, rapid, and efficient method in classification of Rhodiola was developed by Fourier transform near-infrared (FT-NIR) spectroscopy combined with chemometrics analysis. A total of 160 batches of raw spectra were obtained from four different species of Rhodiola by FT-NIR, such as Rhodiola crenulata , Rhodiola fastigiata , Rhodiola kirilowii , and Rhodiola brevipetiolata . After excluding the outliers, different performances of 3 sample dividing methods, 12 spectral preprocessing methods, 2 wavelength selection methods, and 2 modeling evaluation methods were compared. The results indicated that this combination was superior than others in the authenticity identification analysis, which was FT-NIR combined with sample set partitioning based on joint x-y distances (SPXY), standard normal variate transformation (SNV) + Norris-Williams (NW) + 2nd derivative, competitive adaptive reweighted sampling (CARS), and kernel extreme learning machine (KELM). The accuracy (ACCU), sensitivity (SENS), and specificity (SPEC) of the optimal model were all 1, which showed that this combination of FT-NIR and chemometrics methods had the optimal authenticity identification performance. The classification performance of the partial least squares discriminant analysis (PLS-DA) model was slightly lower than KELM model, and PLS-DA model results were ACCU = 0.97, SENS = 0.93, and SPEC = 0.98, respectively. It can be concluded that FT-NIR combined with chemometrics analysis has great potential in authenticity identification and classification of Rhodiola , which can provide a valuable reference for the safety and effectiveness of clinical application of Rhodiola . [ABSTRACT FROM AUTHOR]