Monitoring of the hydrolysis process of bear bile powder using near infrared spectroscopy and chemometrics |
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Affiliation: | 1. Radiation Medicine Engineering Dept., Shahid Beheshti University, Tehran, Iran;2. Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran;1. School of Civil Engineering, Suzhou University of Science and Technology, Suzhou, Jiangsu 215011, China;2. Department of Civil and Environmental Engineering, Rice University, Houston, TX 77005, USA;3. Department of Mechanical Engineering, Rice University, Houston, TX 77005, USA;1. Department of Information Management, Ming Chuan University, No. 5, Deming Rd., Gueishan District, Taoyuan City 333, Taiwan;2. Department of Information Management, Chinese Culture University, No. 55, Huagang Rd., Shihlin District, Taipei City 11114, Taiwan |
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Abstract: | A near infrared (NIR) spectroscopy-based method was developed for monitoring the hydrolysis process of bear bile powder. During the hydrolysis process, samples were collected and measured using both NIR spectrometer and high performance liquid chromatography. The quantitative calibration models were established with the collected NIR spectra and the reference concentrations of tauroursodeoxycholic acid (TUDCA), taurochenodeoxycholic acid (TCDCA), ursodeoxycholic acid (UDCA), and chenodeoxycholic acid (CDCA) using partial least squares regression algorithm. After the models were established and validated, the samples of new batches can be determined rapidly, and the hydrolysis process of bear bile powder can be monitored quantitatively. Additionally, a moving block of standard deviation (MBSD) method was also developed for the endpoint determination of the hydrolysis process. The proposed methods have reduced the laborious workload of process sample analysis significantly, and the fast analytical results have contributed to the understanding and controlling of the bear bile powder hydrolysis process. |
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Keywords: | Hydrolysis process Bear bile powder Near infrared spectroscopy Partial least squares regression Endpoint determination |
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