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. 2014 Jul;10(39):265-70.
doi: 10.4103/0973-1296.137366.

Rapid and undamaged analysis of crude and processed Radix Scrophulariae by Fourier transform infrared spectroscopy coupled with soft independent modeling of class analogy

Huiping Zhu  1 , Gang Cao  2 , Hao Cai  3 , Baochang Cai  3 , Jue Hu  4
Affiliations

Rapid and undamaged analysis of crude and processed Radix Scrophulariae by Fourier transform infrared spectroscopy coupled with soft independent modeling of class analogy

Huiping Zhu et al. Pharmacogn Mag. 2014 Jul.

Abstract

Objective: The main objective of this work is to determine the feasibility of identification of crude and processed Radix Scrophulariae using the Fourier transform infrared spectroscopy couple with soft independent modeling of class analogy (FT-IR-SIMCA).

Materials and methods: A total of 50 different crude Radix Scrophulariae was used to product processed ones. The spectra were acquired by FT-IR spectroscopy using a diffuse reflectance fiber optic probe. For the multivariate analysis, SIMCA was used. Results showed that FT-IR-SIMCA was useful to discriminate the processed Radix Scrophulariae samples from crude samples. These samples could be successfully classified by SIMCA.

Results: In all cases, the recognition and rejection rates were 97.8% and 100%, respectively. When testing with the blind sample that was picked out from the chosen samples, the accuracy was up to 90%.

Conclusion: It means that the methodology is capable of accurately separating processed Radix Scrophulariae from crude samples.

Keywords: Fourier transform infrared; Radix Scrophulariae; quality control; soft independent modeling of class analogy; traditional Chinese medicine.

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Conflict of interest statement

Conflict of Interest: None declared.

Figures

Figure 1
Figure 1
The representative (a) and partial enlargement (b) spectra of crude and processed Radix Scrophulariae
Figure 2
Figure 2
The principal sample analysis score plots generated by the optimized soft independent modeling of class analogy models for the different crude and processed Radix Scrophulariae samples
Figure 3
Figure 3
The histogram of recognition rate and rejection rate of crude drug and processed Radix Scrophulariae samples
Figure 4
Figure 4
Classification results of unknown sample (a) and (b) by soft independent modeling of class analogy models
See this image and copyright information in PMC

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