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Development of Near Infrared Spectroscopy for Rapid Quality Assessment of Red Ginseng 被引量:3

Development of Near Infrared Spectroscopy for Rapid Quality Assessment of Red Ginseng
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摘要 Near infrared spectroscopy(NIRS) was developed as a rapid analysis method for the qualitative and quantitative assessment of the quality of red ginseng. Discriminant analysis(DA) based on principal component analysis and Mahalanobis distance was used to distinguish red ginseng from counterfeits non-destructively. The result shows that the proposed method could distinguish red ginseng from counterfeits correctly and no misclassified sample was found in both training and test sets. The partial least squares(PLS) algorithm was used to predict the sum of ginsenosides Re and Rgl and the content of ginsenoside Rb1. Two calibration models were developed to correlate NIR spectra with the reference values determined by HPLC method. The correlation coefficient(R), the root mean square error of calibration(RMSEC) and the root mean square error of prediction(RMSEP) were as follows: R=0.9827, RMSEC=0.0163%, RMSEP=0.0250% for the sum of ginsenosides Re and Rgl; R=0.9869, RMSEC=0.0156%, RMSEP=0.0256% for content of ginsenoside Rb1. The overall results demonstrate that NIRS coupled with chemometrics could be successfully applied as a rapid, precise and cost-effective method not only to identify the red ginseng from counterfeits but also to determine simultaneously some chemical compositions in red ginseng. Near infrared spectroscopy(NIRS) was developed as a rapid analysis method for the qualitative and quantitative assessment of the quality of red ginseng. Discriminant analysis(DA) based on principal component analysis and Mahalanobis distance was used to distinguish red ginseng from counterfeits non-destructively. The result shows that the proposed method could distinguish red ginseng from counterfeits correctly and no misclassified sample was found in both training and test sets. The partial least squares(PLS) algorithm was used to predict the sum of ginsenosides Re and Rgl and the content of ginsenoside Rb1. Two calibration models were developed to correlate NIR spectra with the reference values determined by HPLC method. The correlation coefficient(R), the root mean square error of calibration(RMSEC) and the root mean square error of prediction(RMSEP) were as follows: R=0.9827, RMSEC=0.0163%, RMSEP=0.0250% for the sum of ginsenosides Re and Rgl; R=0.9869, RMSEC=0.0156%, RMSEP=0.0256% for content of ginsenoside Rb1. The overall results demonstrate that NIRS coupled with chemometrics could be successfully applied as a rapid, precise and cost-effective method not only to identify the red ginseng from counterfeits but also to determine simultaneously some chemical compositions in red ginseng.
出处 《Chemical Research in Chinese Universities》 SCIE CAS CSCD 2009年第5期633-637,共5页 高等学校化学研究(英文版)
关键词 Near infrared soectroscopy Red ginseng Discriminant analysis Partial least squares Near infrared soectroscopy Red ginseng Discriminant analysis Partial least squares
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  • 1Kim H. Y., Kim K. J., Agric. Food Chem., 2007, 55(8), 2816.
  • 2Kimura Y., Sumiyoshi M., Kawahira K., et al., Br. J. Pharmacol., 2006, 148(6), 860.
  • 3Zhang H., Zhou Q. M., Li X. D.,Arch. Pharm. Res., 2006, 29(2), 145.
  • 4China Pharmacopoeia Committee, Pharmacopoeia of the People's Republic of China, 2005 Ed., Vol. I, Chemical Industry Press, Beijing, 2005, 7.
  • 5Rosa S. S., Barata E A., Martins J. M., et al., Pharm. Biomed. Anal., 2008, 47(2), 320.
  • 6Wu Y. W., Sun S. Q., Zhou Q., et al., Pharm. Biomed Anal., 2008, 46(3), 498.
  • 7Bodson C., Rozet E., Ziemons E., et al., Pharm. Biomed. Anal., 2007, 45(2), 356.
  • 8MI H., Guo Y., Li W. L., et al., Chem. Res. Chinese Universities, 2007, 23(1), 116.
  • 9Du L. N., Wu L. H., Lu J. H., et al., Chem. Res. Chinese Universities, 2007, 23(5), 518.
  • 10McCarthy W. J., TQ Analyst User's Guide, Thermo Nicolet Co., Madison, 2000.

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