Near Infrared Spectral Similarity Combined with Variable Se- lection Method in the Quality Control of Flos Lonicerae： A Preliminary Study
This paper indicates the possibility to use near infrared （NIR） spectral similarity as a rapid method to estimate the quality of Flos Lonicerae. Variable selection together with modelling techniques is utilized to select representative variables that are used to calculate the similarity. NIR is used...
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| Published in: | 中国化学：英文版 Vol. 29; no. 11; pp. 2533 - 2540 |
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| Main Author: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | Get full text |
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| Summary: | This paper indicates the possibility to use near infrared （NIR） spectral similarity as a rapid method to estimate the quality of Flos Lonicerae. Variable selection together with modelling techniques is utilized to select representative variables that are used to calculate the similarity. NIR is used to build calibration models to predict the bacte-riostatic activity of Flos Lonicerae. For the determination of the bacteriostatic activity, the in vitro experiment is used. Models are built for the Gram-positive bacteria and also for the Gram-negative bacteria. A genetic algorithm combined with partial least squares regression （GA-PLS） is used to perform the calibration. The results of GA-PLS models are compared to interval partial least squares （iPLS） models, full-spectrum PLS and full-spectrum principal component regression （PCR） models. Then, the variables in the two GA-PLS models are combined and then used to calculate the NIR spectral similarity of samples. The similarity based on the characteristic variables and full spec- trum is used for evaluating the fingerprints of Flos Lonicerae, respectively. The results show that the combination of variable selection method, modelling techniques and similarity analysis might be a powerful tool for quality control of traditional Chinese medicine （TCM）. |
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| Bibliography: | Xin, Ni Meng, Qinghua Li, Yizhen Hu, Yuzhu（a Key Laboratory of Drug Quality Control and Pharmacovigilance, Department of Analytical Chemistry, China Pharmaceutical University, Nanjing, Jiangsu 210009, China b Department of Chemistry, Xuzhou Normal University, Xuzhou, Jiangsu 221116, China） 31-1547/O6 near infrared spectroscopy, similarity, genetic algorithm-partial least squares regression, computational chemistry, analytical methods This paper indicates the possibility to use near infrared （NIR） spectral similarity as a rapid method to estimate the quality of Flos Lonicerae. Variable selection together with modelling techniques is utilized to select representative variables that are used to calculate the similarity. NIR is used to build calibration models to predict the bacte-riostatic activity of Flos Lonicerae. For the determination of the bacteriostatic activity, the in vitro experiment is used. Models are built for the Gram-positive bacteria and also for the Gram-negative bacteria. A genetic algorithm combined with partial least squares regression （GA-PLS） is used to perform the calibration. The results of GA-PLS models are compared to interval partial least squares （iPLS） models, full-spectrum PLS and full-spectrum principal component regression （PCR） models. Then, the variables in the two GA-PLS models are combined and then used to calculate the NIR spectral similarity of samples. The similarity based on the characteristic variables and full spec- trum is used for evaluating the fingerprints of Flos Lonicerae, respectively. The results show that the combination of variable selection method, modelling techniques and similarity analysis might be a powerful tool for quality control of traditional Chinese medicine （TCM）. |
| ISSN: | 1001-604X 1614-7065 |