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Sensors 2015, 15(4), 8749-8763; doi:10.3390/s150408749

A Online NIR Sensor for the Pilot-Scale Extraction Process in Fructus Aurantii Coupled with Single and Ensemble Methods

College of Chinese Medicine, Beijing University of Chinese Medicine, South of Wangjing Middle Ring Road, Chaoyang District, Beijing 100102, China
These authors contribute equally to this work.
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Author to whom correspondence should be addressed.
Academic Editor: Mark A. Arnold
Received: 14 January 2015 / Revised: 30 March 2015 / Accepted: 8 April 2015 / Published: 14 April 2015
(This article belongs to the Special Issue Chemical Sensors based on In Situ Spectroscopy)
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Abstract

Model performance of the partial least squares method (PLS) alone and bagging-PLS was investigated in online near-infrared (NIR) sensor monitoring of pilot-scale extraction process in Fructus aurantii. High-performance liquid chromatography (HPLC) was used as a reference method to identify the active pharmaceutical ingredients: naringin, hesperidin and neohesperidin. Several preprocessing methods and synergy interval partial least squares (SiPLS) and moving window partial least squares (MWPLS) variable selection methods were compared. Single quantification models (PLS) and ensemble methods combined with partial least squares (bagging-PLS) were developed for quantitative analysis of naringin, hesperidin and neohesperidin. SiPLS was compared to SiPLS combined with bagging-PLS. Final results showed the root mean square error of prediction (RMSEP) of bagging-PLS to be lower than that of PLS regression alone. For this reason, an ensemble method of online NIR sensor is here proposed as a means of monitoring the pilot-scale extraction process in Fructus aurantii, which may also constitute a suitable strategy for online NIR monitoring of CHM. View Full-Text
Keywords: online NIR sensor; PLS; bagging-PLS; Fructus aurantii; synergy interval partial least squares online NIR sensor; PLS; bagging-PLS; Fructus aurantii; synergy interval partial least squares
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Pan, X.; Li, Y.; Wu, Z.; Zhang, Q.; Zheng, Z.; Shi, X.; Qiao, Y. A Online NIR Sensor for the Pilot-Scale Extraction Process in Fructus Aurantii Coupled with Single and Ensemble Methods. Sensors 2015, 15, 8749-8763.

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