An approach combining real-time release testing with near-infrared spectroscopy to improve quality control efficiency of Rhizoma paridis

Li, Yerui; Liu, Bowen; Geng, Shengling; Kim, Sung‐Chan; Jin, Young-Woo; Liu, Xuesong; Luan, Lianjun; Wu, Yongjiang; Chen, Yong

doi:10.1016/j.saa.2016.01.001

Cited by 26 publications

(10 citation statements)

References 18 publications

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“…This technique has been commonly used to determine the active compounds of medicinal plants based on spectroscopic data [27]. In the present study, the characteristic band of 1800–600 cm −1 was selected to investigate the prediction ability of PLSR algorithm.…”

Section: Methodsmentioning

confidence: 99%

“…Partial least squares regression (PLSR) is a famous linear regression method to interpret the relationship between spectra data ( X ) and the response vector ( Y ) for quantitative analysis [ 33 ]. This technique has been commonly used to determine the active compounds of medicinal plants based on spectroscopic data [ 27 ]. In the present study, the characteristic band of 1800–600 cm −1 was selected to investigate the prediction ability of PLSR algorithm.…”

Section: Methodsmentioning

confidence: 99%

“…Comparatively, FTIR spectroscopy provides more detailed information, which can represent the overall metabolic profile of samples [ 24 ]. When combined to chemometrics, this technique is employed not only to classify samples but also to predict the content of specific compound by constructing different models [ 25 – 27 ]. In the present study, the chemical variations of different parts and cultivation ages of cultivated G. rigescens were characterized and compared based on HPLC and FTIR techniques.…”

Section: Introductionmentioning

confidence: 99%

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Quantitative and Qualitative Characterization of Gentiana rigescens Franch (Gentianaceae) on Different Parts and Cultivations Years by HPLC and FTIR Spectroscopy

Zhang

Zhao

et al. 2017

Journal of Analytical Methods in Chemistry

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Gentiana rigescens Franch (Gentianaceae) is a famous medicinal plant for treatments of rheumatism, convulsion, and jaundice. Comprehensive investigation of different parts and cultivation years of this plant has not yet been conducted. This study presents the quantitative and qualitative characterization of iridoid glycosides from G. rigescens performed by HPLC and FTIR spectroscopy techniques. The accumulations of loganic acid, swertiamarin, gentiopicroside, and sweroside were determined. Results indicated that their content and distribution in different parts and cultivation years exhibit great variations. Gentiopicroside was identified as the most abundant compound among iridoid glycosides and its highest level was observed in the root of 2-year-old plant. With respect to qualitative variation of metabolic profile, the 1800–800 cm−1 band of FTIR spectra successfully discriminated different parts and cultivation years with the aid of PLS-DA. In addition, combined with PLSR, the feasibility of FTIR spectroscopy for determination of gentiopicroside was investigated by selecting characteristic wavelengths (1800–800 cm−1), which presented a good performance with a residual predictive deviation (RPD) of 3.646. Our results suggested that HPLC and FTIR techniques can complement each other and could be simultaneously applied for comparing and analyzing different parts and cultivation years of G. rigescens.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Quantitative and Qualitative Characterization of Gentiana rigescens Franch (Gentianaceae) on Different Parts and Cultivations Years by HPLC and FTIR Spectroscopy

Zhang

Zhao

et al. 2017

Journal of Analytical Methods in Chemistry

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“…14 Therefore, NIR has been widely applied to quality control of TCM and process analysis depending on its advantages over the years. [15][16][17] Mid-infrared (MIR) spectroscopy complements NIR spectroscopy and covers the region (4000-400 cm À1 ) and contains information on the fundamental molecular vibrations. 18 MIR spectroscopy has also attracted great interest mainly due to its advantages of generating higher sensitivity, selectivity, and higherquality spectral data compared with NIR spectroscopy.…”

Section: Introductionmentioning

confidence: 99%

A combination of near infrared and mid-infrared spectroscopy to improve the determination efficiency of active components in Radix Astragali

Liu

Zhang

et al. 2019

Journal of Near Infrared Spectroscopy

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Radix Astragali is a popular herbal medicine in the pharmaceutical industry, and many studies have confirmed its significant medical value. The objective of this study was to achieve rapid determination of the main active components (astragaloside IV and total astragalosides) in Radix Astragali using near infrared spectroscopy, mid-infrared spectroscopy, and a combination of them. Partial least squares regression was applied to establish quantitative calibration analysis models. According to the prediction results, the combined near infrared and mid-infrared spectroscopy performed better than near infrared and mid-infrared models individually. The determination coefficient and root mean square error of prediction of astragaloside IV and total astragalosides were 0.998, 0.025 and 0.998, 0.098, respectively. It can be concluded that quantitative analysis models constructed by combined near infrared and mid-infrared spectroscopy had superior performance and could be used for rapid determination of main active components in Radix Astragali.

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“…Recently, NIR has been routinely preferred and gradually becomes one of the most efficient online analytical tools for qualitative and quantitative analysis of herb materials, separation monitoring, and extraction process. [89101112131415161718] Therefore, to control the parching process and guarantee the stable quality of parched TCM, NIR spectroscopy in line with the FDAs PAT initiative and guidance was applied in online analysis of TCM parching process. [5]…”

Section: Introductionmentioning

confidence: 99%

Near-infrared spectroscopy as a process analytical technology tool for monitoring the parching process of traditional chinese medicine based on two kinds of chemical indicators

Wang

Liu

et al. 2017

Phcog Mag

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Background:The active ingredients and thus pharmacological efficacy of traditional Chinese medicine (TCM) at different degrees of parching process vary greatly.Objective:Near-infrared spectroscopy (NIR) was used to develop a new method for rapid online analysis of TCM parching process, using two kinds of chemical indicators (5-(hydroxymethyl) furfural [5-HMF] content and 420 nm absorbance) as reference values which were obviously observed and changed in most TCM parching process.Materials and Methods:Three representative TCMs, Areca (Areca catechu L.), Malt (Hordeum Vulgare L.), and Hawthorn (Crataegus pinnatifida Bge.), were used in this study. With partial least squares regression, calibration models of NIR were generated based on two kinds of reference values, i.e. 5-HMF contents measured by high-performance liquid chromatography (HPLC) and 420 nm absorbance measured by ultraviolet–visible spectroscopy (UV/Vis), respectively.Results:In the optimized models for 5-HMF, the root mean square errors of prediction (RMSEP) for Areca, Malt, and Hawthorn was 0.0192, 0.0301, and 0.2600 and correlation coefficients (Rcal) were 99.86%, 99.88%, and 99.88%, respectively. Moreover, in the optimized models using 420 nm absorbance as reference values, the RMSEP for Areca, Malt, and Hawthorn was 0.0229, 0.0096, and 0.0409 and Rcal were 99.69%, 99.81%, and 99.62%, respectively.Conclusions:NIR models with 5-HMF content and 420 nm absorbance as reference values can rapidly and effectively identify three kinds of TCM in different parching processes. This method has great promise to replace current subjective color judgment and time-consuming HPLC or UV/Vis methods and is suitable for rapid online analysis and quality control in TCM industrial manufacturing process.SUMMARY Near-infrared spectroscopy.(NIR) was used to develop a new method for online analysis of traditional Chinese medicine.(TCM) parching processCalibration and validation models of Areca, Malt, and Hawthorn were generated by partial least squares regression using 5.(hydroxymethyl) furfural contents and 420.nm absorbance as reference values, respectively, which were main indicator components during parching process of most TCMThe established NIR models of three TCMs had low root mean square errors of prediction and high correlation coefficientsThe NIR method has great promise for use in TCM industrial manufacturing processes for rapid online analysis and quality control. Abbreviations used: NIR: Near-infrared Spectroscopy; TCM: Traditional Chinese medicine; Areca: Areca catechu L.; Hawthorn: Crataegus pinnatifida Bge.; Malt: Hordeum vulgare L.; 5-HMF: 5-(hydroxymethyl) furfural; PLS: Partial least squares; D: Dimension faction; SLS: Straight line subtraction, MSC: Multiplicative scatter correction; VN: Vector normalization; RMSECV: Root mean square errors of cross-validation; RMSEP: Root mean square errors of validation; Rcal: Correlation coefficients; RPD: Residual predictive deviation; PAT: Process analytical technology; FDA: Food and Drug Administration; ICH: Intern...

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An approach combining real-time release testing with near-infrared spectroscopy to improve quality control efficiency of Rhizoma paridis

Cited by 26 publications

References 18 publications

Quantitative and Qualitative Characterization of Gentiana rigescens Franch (Gentianaceae) on Different Parts and Cultivations Years by HPLC and FTIR Spectroscopy

Quantitative and Qualitative Characterization of Gentiana rigescens Franch (Gentianaceae) on Different Parts and Cultivations Years by HPLC and FTIR Spectroscopy

A combination of near infrared and mid-infrared spectroscopy to improve the determination efficiency of active components in Radix Astragali

Near-infrared spectroscopy as a process analytical technology tool for monitoring the parching process of traditional chinese medicine based on two kinds of chemical indicators

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