High-Sensitivity Determination of Nutrient Elements in Panax notoginseng by Laser-induced Breakdown Spectroscopy and Chemometric Methods

Bibliographic Details
Title: High-Sensitivity Determination of Nutrient Elements in Panax notoginseng by Laser-induced Breakdown Spectroscopy and Chemometric Methods
Authors: Tingting Shen, Weijiao Li, Xi Zhang, Wenwen Kong, Fei Liu, Wei Wang, Jiyu Peng
Source: Molecules, Vol 24, Iss 8, p 1525 (2019)
Publisher Information: MDPI AG, 2019.
Publication Year: 2019
Collection: LCC:Organic chemistry
Subject Terms: Panax notoginseng, nutrient elements, laser-induced breakdown spectroscopy, least absolute shrinkage and selection operator, matrix effect, traditional Chinese medicine, Organic chemistry, QD241-441
More Details: High-accuracy and fast detection of nutritive elements in traditional Chinese medicine Panax notoginseng (PN) is beneficial for providing useful assessment of the healthy alimentation and pharmaceutical value of PN herbs. Laser-induced breakdown spectroscopy (LIBS) was applied for high-accuracy and fast quantitative detection of six nutritive elements in PN samples from eight producing areas. More than 20,000 LIBS spectral variables were obtained to show elemental differences in PN samples. Univariate and multivariate calibrations were used to analyze the quantitative relationship between spectral variables and elements. Multivariate calibration based on full spectra and selected variables by the least absolute shrinkage and selection operator (Lasso) weights was used to compare the prediction ability of the partial least-squares regression (PLS), least-squares support vector machines (LS-SVM), and Lasso models. More than 90 emission lines for elements in PN were found and located. Univariate analysis was negatively interfered by matrix effects. For potassium, calcium, magnesium, zinc, and boron, LS-SVM models based on the selected variables obtained the best prediction performance with Rp values of 0.9546, 0.9176, 0.9412, 0.9665, and 0.9569 and root mean squared error of prediction (RMSEP) of 0.7704 mg/g, 0.0712 mg/g, 0.1000 mg/g, 0.0012 mg/g, and 0.0008 mg/g, respectively. For iron, the Lasso model based on full spectra obtained the best result with an Rp value of 0.9348 and RMSEP of 0.0726 mg/g. The results indicated that the LIBS technique coupled with proper multivariate chemometrics could be an accurate and fast method in the determination of PN nutritive elements for traditional Chinese medicine management and pharmaceutical analysis.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1420-3049
Relation: https://www.mdpi.com/1420-3049/24/8/1525; https://doaj.org/toc/1420-3049
DOI: 10.3390/molecules24081525
Access URL: https://doaj.org/article/8ace89fc78e7428a9ef99eff1d3a0313
Accession Number: edsdoj.8ace89fc78e7428a9ef99eff1d3a0313
Database: Directory of Open Access Journals
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More Details
ISSN:14203049
DOI:10.3390/molecules24081525
Published in:Molecules
Language:English