光谱学与光谱分析 |
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Study on the Application of NAS-Based Algorithm in the NIR Model Optimization |
GENG Ying1, XIANG Bing-ren2, HE Lan1* |
1. National Institutes for Food and Drug Control, Beijing 100050, China 2. Center for Instrumental Analysis, China Pharmaceutical University, Nanjing 210009, China |
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Abstract In this paper, net analysis signal (NAS)-based concept was introduced to the analysis of multi-component Ginkgo biloba leaf extracts. NAS algorithm was utilized for the preprocessing of spectra, and NAS-based two-dimensional correlation analysis was used for the optimization of NIR model building. Simultaneous quantitative models for three flavonol aglycones: quercetin, keampferol and isorhamnetin were established respectively. The NAS vectors calculated using two algorithms introduced from Lorber and Goicoechea and Olivieri (HLA/GO) were applied in the development of calibration models, the reconstructed spectra were used as input of PLS modeling. For the first time, NAS-based two-dimensional correlation spectroscopy was used for wave number selection. The regions appeared in the main diagonal were selected as useful regions for model building. The results implied that two NAS-based preprocessing methods were successfully used for the analysis of quercetin, keampferol and isorhamnetin with a decrease of factor number and an improvement of model robustness. NAS-based algorithm was proven to be a useful tool for the preprocessing of spectra and for optimization of model calibration. The above research showed a practical application value for the NIRS in the analysis of complex multi-component petrochemical medicine with unknown interference.
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Received: 2014-06-27
Accepted: 2014-12-30
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Corresponding Authors:
HE Lan
E-mail: helan@nifdc.org.cn
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