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Journal of Spectroscopy
Volume 2019, Article ID 2467185, 9 pages
https://doi.org/10.1155/2019/2467185
Research Article

Rapid Recognition of Geoherbalism and Authenticity of a Chinese Herb by Data Fusion of Near-Infrared Spectroscopy (NIR) and Mid-Infrared (MIR) Spectroscopy Combined with Chemometrics

1The Modernization Engineering Technology Research Center of Ethnic Minority Medicine of Hubei Province, College of Pharmacy, South-Central University for Nationalities, Wuhan 430074, China
2College of Material and Chemical Engineering, Tongren University, Tongren 554300, Guizhou, China
3State Key Laboratory Breeding Base of Green Chemistry-Synthesis Technology, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310032, China

Correspondence should be addressed to Lu Xu; moc.361@omehcxl and Tianming Yang; nc.ude.ceucs.liam@gnaymt

Received 30 May 2018; Revised 14 December 2018; Accepted 28 March 2019; Published 30 April 2019

Academic Editor: Massimo Lucarini

Copyright © 2019 Haiyan Fu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Fourier transform near-infrared (NIR) spectroscopy and mid-infrared (MIR) spectroscopy play important roles in all fingerprint techniques because of their unique characteristics such as reliability, versatility, precision, and ease of measurement. In this paper, a supervised pattern recognition method based on the PLSDA algorithm by NIR and the NIR-MIR fusion spectra has been established to identify geoherbalism of Angelica dahurica from different regions and authenticity of Corydalis yanhusuo W. T. Wang. Comparing principle component analysis (PCA) cannot successfully identify geographical origins of Angelica dahurica. Linear discriminant analysis (LDA) also hardly distinguishes those origins. Furthermore, the PLSDA model based on the data fusion of NIR and IR was more accurate and efficient. But, the identification of authenticity of Corydalis yanhusuo W. T. Wang was still inaccurate in the PLSDA model. Consequently, data fusion of NIR-MIR original spectra combined with moving window partial least-squares discriminant analysis was firstly used and showed perfect properties on authenticity and adulteration discrimination of Corydalis yanhusuo W. T. Wang. It indicated that data fusion of NIR-MIR spectra combined with MWPLSDA could be considered as the promising tool for rapid discrimination of the geoherbalism and authenticity of more Chinese herbs in the future.