Quantification of bioactive gentiopicroside in the medicinal plant Gentiana scabra Bunge using Near infrared spectroscopy

Yung Kun Chuang, Suming Chen, Yangming Martin Lo, I. Chang Yang, Yu Fan Cheng, Ching Yin Wang, Chao Yin Tsai, Ruey Min Hsieh, Kuo Hsi Wang, Chuo Chun Lai, Wen Chung Chen

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Near infrared (NIR) spectroscopy was employed to perform a quantitative analysis of gentiopicroside, the bioactive component of the medicinal plant Gentiana scabra Bunge. Modified partial least squares regression (MPLSR) and stepwise multiple linear regression (SMLR) calibration models were built using 94 plant tissue culture samples and 136 grown plant samples, respectively, over the full wavelength range (400-2498 nm) and the silicon charge-coupled-device (CCD) sensing band (400-1098 nm). For tissue culture, the smoothing, first-derivative MPLSR model can produce the best effect [calibration set (Rc) = 0.868, standard error of calibration (SEC) = 0.606%, standard error of validation (SEV) = 0.862%] in the wavelength ranges of 900-1000, 1200-1300, and 1600-1700 nm. By contrast, for grown plant samples, the smoothing, second-derivative MPLSR model can produce the best effect (R c = 0.944, SEC = 0.502%, SEV = 0.685%) in the wavelength ranges of 400-500, 1100-1200, 1600-1800, and 2200-2300 nm. With the silicon CCD sensing band, the smoothing, second-derivative, four-wavelength (670, 786,474, and 826 nm) SMLR model showed best predictability (Rc = 0.860, SEC = 0.775%, SEV = 0.848%). This study successfully built spectral calibration models for determining gentiopicroside content at different growth stages of G. scabra Bunge. The specific wavelengths selected within the silicon CCD sensing band can be used in combination with multispectral imaging as a powerful tool for monitoring or inspecting the quality of G. scabra Bunge during cultivation.

Original languageEnglish
Pages (from-to)317-324
Number of pages8
JournalJournal of Food and Drug Analysis
Volume21
Issue number3
DOIs
Publication statusPublished - Sep 2013
Externally publishedYes

Fingerprint

Gentiana scabra
Gentiana
Near-Infrared Spectroscopy
near-infrared spectroscopy
Medicinal Plants
Calibration
medicinal plants
calibration
wavelengths
Silicon
silicon
Least-Squares Analysis
least squares
Linear Models
chemical derivatives
Equipment and Supplies
tissue culture
sampling
plant tissues
gentiopicroside

Keywords

  • Calibration model
  • Gentiana scabra Bunge
  • Gentiopicroside
  • Near infrared spectroscopy

ASJC Scopus subject areas

  • Food Science
  • Pharmacology

Cite this

Quantification of bioactive gentiopicroside in the medicinal plant Gentiana scabra Bunge using Near infrared spectroscopy. / Chuang, Yung Kun; Chen, Suming; Lo, Yangming Martin; Yang, I. Chang; Cheng, Yu Fan; Wang, Ching Yin; Tsai, Chao Yin; Hsieh, Ruey Min; Wang, Kuo Hsi; Lai, Chuo Chun; Chen, Wen Chung.

In: Journal of Food and Drug Analysis, Vol. 21, No. 3, 09.2013, p. 317-324.

Research output: Contribution to journalArticle

Chuang, YK, Chen, S, Lo, YM, Yang, IC, Cheng, YF, Wang, CY, Tsai, CY, Hsieh, RM, Wang, KH, Lai, CC & Chen, WC 2013, 'Quantification of bioactive gentiopicroside in the medicinal plant Gentiana scabra Bunge using Near infrared spectroscopy', Journal of Food and Drug Analysis, vol. 21, no. 3, pp. 317-324. https://doi.org/10.1016/j.jfda.2013.07.011
Chuang, Yung Kun ; Chen, Suming ; Lo, Yangming Martin ; Yang, I. Chang ; Cheng, Yu Fan ; Wang, Ching Yin ; Tsai, Chao Yin ; Hsieh, Ruey Min ; Wang, Kuo Hsi ; Lai, Chuo Chun ; Chen, Wen Chung. / Quantification of bioactive gentiopicroside in the medicinal plant Gentiana scabra Bunge using Near infrared spectroscopy. In: Journal of Food and Drug Analysis. 2013 ; Vol. 21, No. 3. pp. 317-324.
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abstract = "Near infrared (NIR) spectroscopy was employed to perform a quantitative analysis of gentiopicroside, the bioactive component of the medicinal plant Gentiana scabra Bunge. Modified partial least squares regression (MPLSR) and stepwise multiple linear regression (SMLR) calibration models were built using 94 plant tissue culture samples and 136 grown plant samples, respectively, over the full wavelength range (400-2498 nm) and the silicon charge-coupled-device (CCD) sensing band (400-1098 nm). For tissue culture, the smoothing, first-derivative MPLSR model can produce the best effect [calibration set (Rc) = 0.868, standard error of calibration (SEC) = 0.606{\%}, standard error of validation (SEV) = 0.862{\%}] in the wavelength ranges of 900-1000, 1200-1300, and 1600-1700 nm. By contrast, for grown plant samples, the smoothing, second-derivative MPLSR model can produce the best effect (R c = 0.944, SEC = 0.502{\%}, SEV = 0.685{\%}) in the wavelength ranges of 400-500, 1100-1200, 1600-1800, and 2200-2300 nm. With the silicon CCD sensing band, the smoothing, second-derivative, four-wavelength (670, 786,474, and 826 nm) SMLR model showed best predictability (Rc = 0.860, SEC = 0.775{\%}, SEV = 0.848{\%}). This study successfully built spectral calibration models for determining gentiopicroside content at different growth stages of G. scabra Bunge. The specific wavelengths selected within the silicon CCD sensing band can be used in combination with multispectral imaging as a powerful tool for monitoring or inspecting the quality of G. scabra Bunge during cultivation.",
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