System optimisation quantitative model of on‐line NIR: a case of Glycyrrhiza uralensis Fisch extraction process
| العنوان: | System optimisation quantitative model of on‐line NIR: a case of Glycyrrhiza uralensis Fisch extraction process |
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| المؤلفون: | Yanfei Zheng, Lijuan Ma, Jing-Qi Zeng, Xingguo Huang, Yuan Liao, Junjie Cao, Jing Zhang, Zhisheng Wu, Leting Lei, Jinyuan Zhu, Haoran Shen, Zheng Zhou, Ling Lin |
| المصدر: | Phytochemical Analysis. 32:165-171 |
| بيانات النشر: | Wiley, 2020. |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | Mean squared error, Process analytical technology, Plant Science, Residual, 01 natural sciences, Biochemistry, High-performance liquid chromatography, Analytical Chemistry, chemistry.chemical_compound, Drug Discovery, Glycyrrhiza, Glycyrrhiza uralensis, Chromatography, High Pressure Liquid, Plants, Medicinal, Chromatography, biology, Plant Extracts, Content determination, 010401 analytical chemistry, Extraction (chemistry), General Medicine, Glycyrrhizic Acid, biology.organism_classification, 0104 chemical sciences, 010404 medicinal & biomolecular chemistry, Complementary and alternative medicine, chemistry, Molecular Medicine, Liquiritin, Food Science |
| الوصف: | Introduction The on-line analysis of active pharmaceutical ingredients (APIs) during the extraction process in herbal medicine is a challenge. Establishing a reliable and robust model is a critical procedure for the industrial application of on-line near-infrared (NIR) technology. Objective To evaluate the advantages of on-line NIR model development using system optimisation strategy, Glycyrrhiza uralensis Fisch was used as a case. The content of liquiritin and glycyrrhizic acid was monitored during pilot scale extraction process of Glycyrrhiza uralensis Fisch in three batches. Methods High-performance liquid chromatography (HPLC) was used as reference method for content determination of liquiritin and glycyrrhizic acid. The quantitative models of on-line NIR were developed by system optimisation of processing trajectory. For comparison, the models were simultaneously developed by stepwise optimisation. Moreover, the modelling parameters obtained through system optimisation and stepwise optimisation were reused in three batches. Root mean square error of prediction (RMSEP) and residual predictive deviation (RPD) were used to assess the model quality. Results The average values of RMSEP and RPD of systematic model for liquiritin in three batches were 0.0361, 4.1525 (first batch), 0.0348, 4.7286 (second batch) and 0.0311, 4.9686 (third batch), respectively. In addition, the modelling parameters of systematic model for glycyrrhizic acid in three batches were same, and the average values of RMSEP and RPD were 0.0665 and 5.2751, respectively. The predictive performance and robustness of systematic models for the three batches were better than the comparison models. Conclusion The work demonstrated that system optimisation quantitative model of on-line NIR could be used to determine the contents of liquiritin and glycyrrhizic acid during Glycyrrhiza uralensis Fisch extraction process. |
| تدمد: | 1099-1565 0958-0344 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4cc8591f776157c271f1be9196832228 https://doi.org/10.1002/pca.2919 |
| حقوق: | CLOSED |
| رقم الأكسشن: | edsair.doi.dedup.....4cc8591f776157c271f1be9196832228 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 10991565 09580344 |
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