Planta Med 2016; 82(01/02): 154-162
DOI: 10.1055/s-0035-1558085
Analytical Studies
Original Papers
Georg Thieme Verlag KG Stuttgart · New York

Comparison of Ensemble Strategies in Online NIR for Monitoring the Extraction Process of Pericarpium Citri Reticulatae Based on Different Variable Selections

Zheng Zhou
1   Beijing University of Chinese Medicine, Beijing, China
4   Fujian University of Traditional Chinese Medicine, Fujian, China
,
Yang Li
1   Beijing University of Chinese Medicine, Beijing, China
,
Qiao Zhang
1   Beijing University of Chinese Medicine, Beijing, China
,
Xinyuan Shi
1   Beijing University of Chinese Medicine, Beijing, China
2   Key Laboratory of TCM-information Engineering of State Administration of TCM, Beijing, China
3   Beijing Key Laboratory for Basic and Development Research on Chinese Medicine, Beijing, China
,
Zhisheng Wu
1   Beijing University of Chinese Medicine, Beijing, China
2   Key Laboratory of TCM-information Engineering of State Administration of TCM, Beijing, China
3   Beijing Key Laboratory for Basic and Development Research on Chinese Medicine, Beijing, China
,
Yanjiang Qiao
1   Beijing University of Chinese Medicine, Beijing, China
2   Key Laboratory of TCM-information Engineering of State Administration of TCM, Beijing, China
3   Beijing Key Laboratory for Basic and Development Research on Chinese Medicine, Beijing, China
› Author Affiliations
Further Information

Publication History

received 08 February 2015
revised 10 July 2015

accepted 20 August 2015

Publication Date:
20 October 2015 (online)

Zoom Image

Abstract

Different ensemble strategies were compared in online near-infrared models for monitoring active pharmaceutical ingredients of Traditional Chinese Medicine. Bagging partial least square regression and boosting partial least square regression were adopted to near-infrared models, to determine hesperidin and nobiletin content during the extraction process of Pericarpium Citri Reticulatae in a pilot scale system. Different pretreatment methods were investigated, including Savitzky-Golay smoothing, derivatives, multiplicative scatter correction, standard normal variate, normalize, and combinations of them. Two different variable selection methods, including synergy interval partial least squares and backward interval partial least squares algorithms, were performed. Based on the result of the synergy interval partial least squares algorithm, bagging partial least square regression and boosting partial least square regression were adopted into the quantitative analysis. The results demonstrated that the established approach could be applied for rapid determination and real-time monitoring of hesperidin and nobiletin in Pericarpium Citri Reticulatae (Citrus reticulata) during the extraction process. Comparing the results, the boosting partial least square regression provided a slightly better accuracy than the bagging partial least square regression. Finally, this paper provides a promising ensemble strategy on online near-infrared models in Chinese medicine.