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Quantitative analysis of two adulterants in Cynanchum stauntonii by near-infrared spectroscopy combined with multi-variate calibrations

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Abstract

Authentication of traditional Chinese medicines (TCMs) has become important because they can be adulterated with relatively cheap herbal medicines similar in appearance. Detection of such adulterated samples is needed because their presence is likely to reduce the pharmacological potency of the original TCM and, in the worst cases, the samples may be harmful. The aim of this study was to develop a rapid near-infrared spectroscopy (NIRS) analytical method which was supported by multi-variate calibration, e.g. partial least squares regression (PLSR) and radial basis function artificial neural networks (RBF-ANN), in order to quantify the TCM and the adulterants. In this work, Cynanchum stauntonii (CS), a commonly used TCM, in mixtures with one or two adulterants — two morphological types of TCM, Cynanchum atrati (CA) and Cynanchum paniculati (CP), were determined using NIR reflectance spectroscopy. The three sample sets, CS adulterated with CA or CP, and CS with both CA and CP, were measured in the range of 800–2500 nm. Both PLSR and RBF-ANN calibration models provided satisfactory results, even at an adulteration level of 5 mass %, but the RBF-ANN models with better root mean square error of prediction (RMSEP) values for CS, CA, and CP arguably performed better. Consequently, this work demonstrates that the NIR method of sampling complex mixtures of similar substances such as CS adulterated by CA and/or CP is capable of producing data suitable for the quantitative analysis of mixtures consisting of the original TCM adulterated by one or two similar substances, provided the spectral data are interrogated by multi-variate methods of data analysis such as PLS or RBF-ANN.

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References

  • Balabin, R. M., Safieva, R. Z., & Lomakina, E. I. (2007). Comparison of linear and nonlinear calibration models based on near infrared (NIR) spectroscopy data for gasoline properties prediction. Chemometrics and Intelligent Laboratory Systems, 88, 183–188. DOI: 10.1016/j.chemolab.2007.04.006.

    Article  CAS  Google Scholar 

  • Balabin, R. M., Safieva, R. Z., & Lomakina, E. I. (2008). Wavelet neural network (WNN) approach for calibration model building based on gasoline near infrared (NIR) spectra. Chemometrics and Intelligent Laboratory Systems, 93, 58–62. DOI: 10.1016/j.chemolab.2008.04.003.

    Article  CAS  Google Scholar 

  • Balabin, R. M., & Lomakina, E. I. (2011). Support vector machine regression (SVR/LS-SVM)-an alterative to neural networks (ANN) for analytical chemistry? Comparison of nonlinear methods on near infrared (NIR) spectroscopy data. Analyst, 136, 1703–1712. DOI: 10.1039/c0an00387e.

    Article  CAS  Google Scholar 

  • Barnes, R. J., Dhanoa, M. S., & Lister, S. J. (1989). Standard normal variate transformation and de-trending of nearinfrared diffuse reflectance spectra. Applied Spectroscopy, 43, 772–777. DOI: 10.1366/0003702894202201.

    Article  CAS  Google Scholar 

  • Blanco, M., Coello, J., Iturriaga, H., Maspoch, S., & Serrano, D. (1998). Near-infrared analytical control of pharmaceuticals. A single calibration model from mixed phase to coated tablets. Analyst, 123, 2307–2312. DOI: 10.1039/a805946b.

    Article  CAS  Google Scholar 

  • Burns, D. A., & Ciurczak, E. W. (Eds.) (2001). Handbook of near-infrared analysis (2nd ed.) (Practical spectroscopy series, Vol. 27). New York, NY, USA: Marcel Dekker.

    Google Scholar 

  • Camastra, F., & Vinciarelli, A. (2008). Machine learning for audio, image and video analysis: Theory and applications. London, UK: Springer.

    Book  Google Scholar 

  • Cianchino, V., Acosta, G., Ortega, C., Martínez, L. D., & Gomez, M. R. (2008). Analysis of potential adulteration in herbal medicines and dietary supplements for the weight control by capillary electrophoresis. Food Chemistry, 108, 1075–1081. DOI: 10.1016/j.foodchem.2007.11.042.

    Article  CAS  Google Scholar 

  • Despagne, F., & Massart, D. L. (1998). Neural networks in multivariate calibration. Analyst, 123, 157R–178R. DOI: 10.1039/a805562i.

    Article  CAS  Google Scholar 

  • Duda, R. O., Hart, P. E., & Stork, D. G. (2001). Pattern classification (2nd ed.). New York, NY, USA: Wiley.

    Google Scholar 

  • European Medicines Agency (2011). Guideline on quality of herbal medicinal products/traditional herbal medicinal products (EMA/CPMP/QWP/2819/00 Rev. 2). London, UK: European Medicines Agency.

    Google Scholar 

  • Felizardo, P., Baptista, P., Menezes, J. C., & Correia, M. J. N. (2007). Multivariate near infrared spectroscopy models for predicting methanol and water content in biodiesel. Analytica Chimica Acta, 595, 107–113. DOI: 10.1016/j.aca.2007.02.050.

    Article  CAS  Google Scholar 

  • Geladi, P., MacDougall, D., & Martens, H. (1985). Linearization and scatter-correction for near-infrared reflectance spectra of meat. Applied Spectroscopy, 39, 491–500. DOI: 10.1366/0003702854248656.

    Article  Google Scholar 

  • Geladi, P., & Kowalski, B. R. (1986). Partial least-squares regression: A tutorial. Analytica Chimica Acta, 185, 1–17. DOI: 10.1016/0003-2670(86)80028-9.

    Article  CAS  Google Scholar 

  • Gorry, P. A. (1990). General least-squares smoothing and differentiation by the convolution (Savitzky-Golay) method. Analytical Chemistry, 62, 570–573. DOI: 10.1021/ac00205a007.

    Article  CAS  Google Scholar 

  • He, Y. (2005). Practical pharmacy (pp. 94–95). Beijing, China: Beijing Science and Technology Press.

    Google Scholar 

  • Kuriakose, S., Thankappan, X., Joe, H., & Venkataraman, V. (2010). Detection and quantification of adulteration in sandalwood oil through near infrared spectroscopy. Analyst, 135, 2676–2681. DOI: 10.1039/c0an00261e.

    Article  CAS  Google Scholar 

  • Laasonen, M., Harmia-Pulkkinen, T., Simard, C. L., Michiels, E., Räsänen, M., & Vuorela, H. (2002). Fast identification of Echinacea purpurea dried roots using near-infrared spectroscopy. Analytical Chemistry, 74, 2493–2499. DOI: 10.1021/ac011108f.

    Article  CAS  Google Scholar 

  • Lai, Y., Ni, Y., & Kokot, S. (2011). Discrimination of Rhizoma Corydalis from two sources by near-infrared spectroscopy supported by the wavelet transform and least-squares support vector machine methods. Virbrational Spectroscopy, 56, 154–160. DOI: 10.1016/j.vibspec.2011.01.007.

    Article  CAS  Google Scholar 

  • Li, W., Xing, L., Cai, Y., & Qu, H. (2011). Classification and quantification analysis of Radix scutellariae from different origins with near infrared diffuse reflection spectroscopy. Virbrational Spectroscopy, 55, 58–64. DOI: 10.1016/j.vibspec.2010.07.004.

    Article  CAS  Google Scholar 

  • Liang, Q., Qu, J., Luo, G., & Wang, Y. (2006). Rapid and reliable determination of illegal adulterant in herbal medicines and dietary supplements by LC/MS/MS. Journal of Pharmaceutical and Biomedical Analysis, 40, 305–311. DOI: 10.1016/j.jpba.2005.07.035.

    Article  CAS  Google Scholar 

  • Liao, Y. (2008). Discrimination of Cynanchum stauntonii and Cynanchum atrati. Shiyong Zhongyiyao Zazhi/Journal of Practical Traditional Chinese Medicine, 24, 326–327. (in Chinese)

    Google Scholar 

  • Liu, L. (2002). Identification of Cynanchum stauntonii, congeneric plants and its adulterants using ultraviolet derivative spectroscopy. Zhong Caoyao/Chinese Traditional and Herbal Drugs, 33, 169–170. (in Chinese)

    Google Scholar 

  • Liu, Y., Barton, F. E., II., Lyon, B. G., Windham, W. R., & Lyon, C. E. (2004). Two-dimensional correlation analysis of visible/near-infrared spectral intensity variations of chicken breasts with various chilled and frozen storages. Journal of Agricultural and Food Chemistry, 52, 505–510. DOI: 10.1021/jf0303464.

    Article  CAS  Google Scholar 

  • Lu, W., Yuan, H., Xu, G., & Qiang, D. (2000). Modern near infrared spectroscopy analysis technology (pp. 14–16). Beijing, China: Chinese Petroleum and Chemical Industry Publishing House.

    Google Scholar 

  • Martens, H., & Naes, T. (1989). Multivariate calibration. Chichester, UK: Wiley.

    Google Scholar 

  • Osborne, B. G., Fearn, T., & Hindle, P. H. (1993). Practical NIR spectroscopy with applications in food and beverage analysis (2nd ed.) (Longman food technology series). Harlow, UK: Longman Scientific & Technical.

    Google Scholar 

  • Pan, X. (2005). Identification of the same genera and confused varieties of plants: Cynanchum stauntonii, Cynanchum atrati and Cynanchum paniculati. Shoudou Yiyao/Capital Medicine, 12, 43–44. (in Chinese)

    Google Scholar 

  • Peiris, K. H. S., Pumphrey, M. O., & Dowell, F. E. (2009). NIR absorbance characteristics of deoxynivalenol and of sound and Fusarium-damaged wheat kernels. Journal of Near Infrared Spectroscopy, 17, 213–221. DOI: 10.1255/jnirs.846.

    Article  CAS  Google Scholar 

  • Qiu, S. (1994). Chemical constituents of Cynanchum stauntonii. Zhongguo Zhongyao Zazhi/China Journal of Chinese Materia Medica, 19, 488–489. (in Chinese)

    CAS  Google Scholar 

  • Savitzky, A., & Golay, M. J. E. (1964). Smoothing and differentiation of data by simplified least squares procedures. Analytical Chemistry, 36, 1627–1639. DOI: 10.1021/ac60214a047.

    Article  CAS  Google Scholar 

  • Wang, C. Z., Ni, M., Sun, S., Li, X. L., He, H., Mehendale, S. R., & Yuan, C. S. (2009). Detection of adulteration of notoginseng root extract with other Panax species by quantitative HPLC coupled with PCA. Journal of Agricultural and Food Chemistry, 57, 2363–2367. DOI: 10.1021/jf803320d.

    Article  CAS  Google Scholar 

  • Wang, P., Qin, H. L., Zhang, L., Li, Z. H., Wang, Y. H., & Zhu, H. B. (2004). Steroids from the roots of Cynanchum stauntonii. Planta Medica, 70, 1075–1079. DOI: 10.1055/s-2004-832650.

    Article  CAS  Google Scholar 

  • Wold, S., Ruhe, A., Wold, H., & Dunn, W. J., III. (1984). The collinearity problem in linear regression. The partial least squares (PLS) approach to generalized inverses. SIAM Journal on Scientific and Statistical Computing, 5, 735–743. DOI: 10.1137/0905052.

    Article  Google Scholar 

  • Workman, J. (2002). How to interpret near infrared spectra for a variety of applications. Item Number: SHIR100, Spectroscopy Audio Seminar Series [CD].

  • Wu, D., Nie, P., Cuello, J., He, Y., Wang, Z., & Wu, H. (2011). Application of visible and near infrared spectroscopy for rapid and non-invasive quantification of common adulterants in Spirulina powder. Journal of Food Engineering, 102, 278–286. DOI: 10.1016/j.jfoodeng.2010.09.002.

    Article  CAS  Google Scholar 

  • Xue, F., & Chen, Y. (1994). Identification of Cynanchum stauntonii, Cynanchum atrati, Cynanchum paniculati and adulterants using ultraviolet spectroscopy. Shandong Zhongyi Zazhi/Shandong Journal of Traditional Chinese Medicine, 13, 362. (in Chinese)

    Google Scholar 

  • Yang, Z. C, Wang, B. C., Yang, X. S., & Wang, Q. (2005). Chemical composition of the volatile oil from Cynanchum stauntonii and its activities of anti-infulenza virus. Colloids and Surfaces B: Biointerfaces, 43, 198–202. DOI: 10.1016/j.colsurfb.2005.05.003.

    Article  CAS  Google Scholar 

  • Yap, K. Y. L., Chan, S. Y., & Lim, C. S. (2007). Authentication of traditional Chinese medicine using infrared spectroscopy: distinguishing between ginseng and its morphological fakes. Journal of Biomedical Science, 14, 265–273. DOI: 10.1007/s11373-006-9133-3.

    Article  CAS  Google Scholar 

  • Yu, H., Zhong, S., Chan, K., & Berry, M. I. (1995). Pharmacognostical investigation on traditional Chinese medicinal herbs: identification of four herbs from the UK market. Journal of Pharmacy and Pharmacology, 47, 1129.

    Google Scholar 

  • Zhang, L., & Nie, L. (2010). Discrimination of geographical origin and adulteration of Radix astragali using Fourier transform infrared spectroscopy and chemometric methods. Phytochemical Analysis, 21, 609–615. DOI: 10.1002/pca.1242.

    Article  CAS  Google Scholar 

  • Zhou, D., & Li, Y. (2010). Identification and comparison of six varieties of herbs: Cynanchum stauntonii, Cynanchum atrati and Cynanchum paniculati, etc. Zhongguo Zhongyiyao Xiandai Yuancheng Jiaoyu/Chinese Medicine Modern Distance Education of China, 8, 80–82. (in Chinese)

    Google Scholar 

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Authors and Affiliations

  1. State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang, 330047, China

    Wen-Jiang Dong & Yong-Nian Ni

  2. Department of Chemistry, Nanchang University, Nanchang, 330031, China

    Yong-Nian Ni

  3. School of Chemistry, Physics and Mechanical Engineering, Science and Engineering Faculty, Queensland University of Technology, Brisbane, 4001, Australia

    Serge Kokot

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  1. Wen-Jiang Dong
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  2. Yong-Nian Ni
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  3. Serge Kokot
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Correspondence to Yong-Nian Ni.

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Dong, WJ., Ni, YN. & Kokot, S. Quantitative analysis of two adulterants in Cynanchum stauntonii by near-infrared spectroscopy combined with multi-variate calibrations. Chem. Pap. 66, 1083–1091 (2012). https://doi.org/10.2478/s11696-012-0231-6

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