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. 2020 Nov 4:2020:8847277.
doi: 10.1155/2020/8847277. eCollection 2020.

Near-Infrared Spectroscopy as a Process Analytical Technology Tool for Monitoring the Steaming Process of Gastrodiae rhizoma with Multiparameters and Chemometrics

Yamin Zuo  1 , Jing Yang  2 , Chen Li  1 , Xuehua Deng  1 , Shengsheng Zhang  3 , Qing Wu  3
Affiliations

Near-Infrared Spectroscopy as a Process Analytical Technology Tool for Monitoring the Steaming Process of Gastrodiae rhizoma with Multiparameters and Chemometrics

Yamin Zuo et al. J Anal Methods Chem. .

Abstract

Steaming is a vital unit operation in traditional Chinese medicine (TCM), which greatly affects the active ingredients and the pharmacological efficacy of the products. Near-infrared (NIR) spectroscopy has already been widely used as a strong process analytical technology (PAT) tool. In this study, the potential usage of NIR spectroscopy to monitor the steaming process of Gastrodiae rhizoma was explored. About 10 lab scale batches were employed to construct quantitative models to determine four chemical ingredients and moisture change during the steaming process. Gastrodin, p-hydroxybenzyl alcohol, parishin B, and parishin A were modeled by different multivariate calibration models (SMLR and PLS), while the content of the moisture was modeled by principal component regression (PCR). In the optimized models, the root mean square errors of prediction (RMSEP) for gastrodin, p-hydroxybenzyl alcohol, parishin B, parishin A, and moisture were 0.0181, 0.0143, 0.0132, 0.0244, and 2.15, respectively, and correlation coefficients (R p 2) were 0.9591, 0.9307, 0.9309, 0.9277, and 0.9201, respectively. Three other batches' results revealed that the accuracy of the model was acceptable and that was specific for next drying step. In addition, the results demonstrated the method was reliable in process performance and robustness. This method holds a great promise to replace current subjective color judgment and time-consuming HPLC or UV/Vis methods and is suitable for rapid online monitoring and quality control in the TCM industrial steaming process.

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Conflict of interest statement

The authors declare that they have no conflicts of interest.

Figures

Figure 1
Figure 1
The representative HPLC chromatogram of gastrodin (1), p-hydroxybenzyl alcohol (2), parishin B (3), and parishin A (4) in Gastrodiae rhizoma steaming samples (A) and standard solution (B).
Figure 2
Figure 2
(a) Raw NIR spectra and (b) spectra preprocessed by MSC + FD/SG of all samples collected from the steaming process.
Figure 3
Figure 3
The efficient spectral intervals selected by si-PLS for the prediction of four phenolic compounds: (a) gastrodin, (b) p-hydroxybenzyl alcohol, (c) parishin B, and (d) parishin A.
Figure 4
Figure 4
The PCR model of moisture content's spectrum outlier selected according to Mahalanobis distance.
Figure 5
Figure 5
Spectra preprocessed by MSC + SD/SG of all samples and the efficient spectral intervals selected by PCR for the prediction of moisture content.
Figure 6
Figure 6
The first loading factor spectra of the PCR model for the moisture content prediction.
Figure 7
Figure 7
Prediction results of the moisture content models.
Figure 8
Figure 8
Prediction results of the four PLS models: (a) gastrodin, (b) p-hydroxybenzyl alcohol, (c) parishin B, and (d) parishin A.
Figure 9
Figure 9
Comparison of the online NIR prediction values with the reference values of the steaming process of the test batch.
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