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Quantitative Model Establishment for Volatile Oils from Rhizoma Wenyujin Concisum by Near-infrared Spectrometry / 中国药师
China Pharmacist ; (12): 1866-1869, 2017.
Artigo em Chinês | WPRIM (Pacífico Ocidental) | ID: wpr-658234
Biblioteca responsável: WPRO
ABSTRACT

Objective:

To established a near-infrared spectroscopy quantitative model for the rapid determination of volatile oils from Rhizoma wenyujin concisum.

Methods:

Firstly, the volatile oils from Rhizoma wenyujin was determined by the distillation method described in Chinese Pharmacopoeia. The quantitative calibration model was established and optimized by fourier transformation near-infrared spectroscopy ( FT-NIR) combined with partial least square ( PLS) regression. The calibration model was evaluated by the coef-ficient (r), root-mean-square error of calibration (RMSEC) and root mean square of cross-validation (RMSECV) of the calibration model as well as the root mean square of prediction ( RMSEP) of prediction model.

Results:

In the combination of FT-NIR and PLS regression, the spectrum of 7189-4227 cm-1 , 8813-7478 cm-1 and"second spectrum+MSC" were chosen to establishe and optimize the quantitative calibration model. For the quantitative calibration model, the r, RMSEC and RMSECV of volatile oils was 0. 9769, 0. 0907 and 0. 3773, respectively. For the prediction model, the r and RMSEP of volatile oils was 0. 9053 and 0. 1960, respective-ly.

Conclusion:

The established near-infrared spectroscopy quantitative model is relatively stable, accurate and reliable in the simulta-neous quantitative analysis of volatile oils, and is expected to be used for the rapid determination of volatile oils from Rhizoma wenyujin concisum.

Texto completo: Disponível Base de dados: WPRIM (Pacífico Ocidental) Tipo de estudo: Estudo prognóstico Idioma: Chinês Revista: China Pharmacist Ano de publicação: 2017 Tipo de documento: Artigo
Texto completo: Disponível Base de dados: WPRIM (Pacífico Ocidental) Tipo de estudo: Estudo prognóstico Idioma: Chinês Revista: China Pharmacist Ano de publicação: 2017 Tipo de documento: Artigo
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