Validation of a NIR quantification method for the determination of chlorogenic acid in Lonicera japonica solution in ethanol precipitation process

Wu, Zhisheng; Xu, Bing; Du, Min; Sui, Chenglin; Shi, Xinyuan; Qiao, Yanjiang

doi:10.1016/j.jpba.2011.12.005

Cited by 52 publications

(29 citation statements)

References 13 publications

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“…It generally refers to evaluation of raw materials, CS extraction, ultra¯ltration, oxidation, precipitation, drying, grinding and packaging. Above all, ethanol precipitation which will lead to an unstable product quality and di®erences between batches is the most important unit used in industrial production [11][12][13][14] and the relevance between NIRS and CS is still unclear.…”

Section: Introductionmentioning

confidence: 99%

The relevance study of effective information between near infrared spectroscopy and chondroitin sulfate in ethanol precipitation process

Ding

et al. 2014

J. Innov. Opt. Health Sci.

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Near infrared spectroscopy (NIRS) is based on molecular overtone and combination vibrations. It is di±cult to assign speci¯c features under complicated system. So it is necessary to¯nd the relevance between NIRS and target compound. For this purpose, the chondroitin sulfate (CS) ethanol precipitation process was selected as the research model, and 90 samples of 5 di®erent batches were collected and the content of CS was determined by modi¯ed carbazole method. The relevance between NIRS and CS was studied throughout optical pathlength, pretreatment methods and variables selection methods. In conclusion, the¯rst derivative with Savitzky-Golay (SG) smoothing was selected as the best pretreatment, and the best spectral region was selected using interval partial least squares (iPLS) method under 1 mm optical cell. A multivariate calibration model was established using PLS algorithm for determining the content of CS, and the root mean square error of prediction (RMSEP) is 3.934 gÁL À1 . This method will have great potential in process analytical technology in the future.

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Section: Introductionmentioning

confidence: 99%

The relevance study of effective information between near infrared spectroscopy and chondroitin sulfate in ethanol precipitation process

Ding

et al. 2014

J. Innov. Opt. Health Sci.

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“…As these traditional model statistics are proven insufficient to validate a method [22][23][24][25][26][27][28], the final decision about the most qualified model was made based on the information derived from the accuracy profiles calculated in the validation step.…”

Section: Development Of the Pls Quantification Modelsmentioning

confidence: 99%

“…This validation procedure, introduced by the Société Française des Sciences et Techniques Pharmaceutiques (SFSTP) [19], [20] is widely accepted in the pharmaceutical field as can be derived from the numerous applications in literature [10], [21]- [28]. To our best knowledge, no applications are published from the consumer goods industry, making this a cutting-edge approach in the business.…”

Section: Introductionmentioning

confidence: 99%

Development and validation of an at-line fast and non-destructive Raman spectroscopic method for the quantification of multiple components in liquid detergent compositions

Brouckaert

Uyttersprot

Broeckx

et al. 2016

Analytica Chimica Acta

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Implementation of process analytical technology (PAT) tools in the manufacturing process of liquid detergent compositions should allow fast and non-destructive evaluation of the product quality. The aim of this study was to develop and validate a rapid method for quantifying the chemical compounds of five washing liquid precursors. Raman spectroscopy was applied in combination with a two-step multivariate modeling procedure. In first instance, a SIMCA (Soft Independent Modeling of Class Analogy) model was developed and validated, allowing the distinction between the different laundry detergents. Once the product was correctly identified, it was aimed at predicting the concentration of its individual components using partial least squares (PLS) models. Raman spectra were collected at-line with a total acquisition time of 20 seconds, using a non-contact fiber-optic probe. 3The SIMCA model was perfectly capable of differentiating between the classes of the laundry liquid precursors. Per detergent, the concentration of at least three main ingredients could be predicted with a recovery between 98 % and 102 % and a standard deviation below 2.5 %. Accuracy profiles based on the analysis results of validation samples were then calculated to prove the reliability of the developed regression models. β-expectation tolerance intervals were calculated for each model and for each validated concentration level. The acceptance limits were set at 5 % relative bias, indicating that at least 95 % of future measurements should not deviate more than 5 % from the true value. Furthermore, based on the data of the accuracy profiles, the measurement uncertainty was determined.The developed Raman spectroscopic method demonstrated to be able to rapidly and adequately determine the concentration of the components of interest in the liquid detergent compositions at-line. Keywords

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“…[9][10][11][12][13][14][15] NIR spectroscopy has also shown great power and gained wide acceptance in TCM manufacturing industry. 11,16 The most wellknown applications of NIR spectroscopy in the manufacturing processes of TCM include the separation monitoring, 17 end point judgement of extraction process, [18][19][20] alcohol precipitation monitoring, 21 etc. Obviously, NIR spectroscopy is a promise technology for the understanding of the TCM manufacturing processes.…”

Section: Introductionmentioning

confidence: 99%

Rapid monitoring the water extraction process of Radix Paeoniae Alba using near infrared spectroscopy

Tian

Zang

et al. 2017

J. Innov. Opt. Health Sci.

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Near infrared (NIR) spectroscopy has been developed into one of the most important process analytical techniques (PAT) in a wide¯eld of applications. The feasibility of NIR spectroscopy with partial least square regression (PLSR) to monitor the concentration of paeoni°orin, albi-°o rin, gallic acid, and benzoyl paeoni°orin during the water extraction process of Radix Paeoniae Alba was demonstrated and veri¯ed in this work. NIR spectra were collected in transmission mode and pretreated with smoothing and/or derivative, and then quantitative models were built up using PLSR. Interval partial least squares (iPLS) method was used for the selection of spectral variables. Determination coe±cients (R 2 cal and R 2 pred ), root mean squares error of prediction (RMSEP), root mean squares error of calibration (RMSEC), and residual predictive deviation (RPD) were applied to verify the performance of the models, and the corresponding values were 0.9873 and 0.9855, 0.0487 mg/mL, 0.0545 mg/mL and 8.4 for paeoni°orin; 0.9879, 0.9888, 0.0303 mg/mL, 0.0321 mg/mL and 9.1 for albi°orin; 0.9696, 0.9644, 0.0140 mg/mL, 0.0145 mg/mL and 5.1 for gallic acid; 0.9794, 0.9781, 0.00169 mg/mL, 0.00171 mg/mL and 6.9 for benzoyl paeoni°orin, respectively. The results turned out that this approach was very e±cient and environmentally friendly for the quantitative monitoring of the water extraction process of Radix Paeoniae Alba.

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Validation of a NIR quantification method for the determination of chlorogenic acid in Lonicera japonica solution in ethanol precipitation process

Cited by 52 publications

References 13 publications

The relevance study of effective information between near infrared spectroscopy and chondroitin sulfate in ethanol precipitation process

The relevance study of effective information between near infrared spectroscopy and chondroitin sulfate in ethanol precipitation process

Development and validation of an at-line fast and non-destructive Raman spectroscopic method for the quantification of multiple components in liquid detergent compositions

Rapid monitoring the water extraction process of Radix Paeoniae Alba using near infrared spectroscopy

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