| 光谱学与光谱分析 |
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| Determination of Hesperidin Content in Guogongjiu Medicinal Wine Based on NIR Spectrometry and Least Squares Support Vector Machines |
| ZHU Xiang-rong1, 3, SHAN Yang1, LI Gao-yang1, FAN Qiang2, SHI Xin-yuan2, QIAO Yan-jiang2, ZHANG Zhuo-yong3* |
1. Hunan Provincial Research Institute of Agricultural Product Processing, Changsha 410125, China
2. School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing 100102, China
3. Department of Chemistry, Capital Normal University, Beijing 100037, China |
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Abstract Near-infrared spectroscopy (NIRS) combined with least squares support vector machines (LS-SVM) was used to establish a new method for the determination of the hesperidin content in guogongjiu medicinal wine. Firstly, training set was partitioned by Kernard-Stone (KS) algorithm. Secondly, spectral pretreatment methods were discussed in detail, comparing smoothing, rangescaling, autoscaling, first derivative, second derivative, along with those methods combined. Smoothing, first derivative and rangescaling were used for the pretreatment of the NIR spectra of guogongjiu medicinal wine. Thirdly, the effective interval was selected for 8 211-8 312 and 9 712-9 808 cm-1 by synergy interval partial least squares (siPLS). Finally, the model was established by LS-SVM, the root mean square error of cross validation (RMSECV) is 0.001, root mean square error of prediction (RMSEP) is 0.004, and relative deviation of predicting set is less than 5%. It was compared with siPLS, radial basis function neural network (RBF-NN), and SVM, The result shows that the method is rapid, non-destructive, and credible. It is an effective measurement for determining the hesperidin content in guogongjiu medicinal wine.
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Received: 2008-08-02
Accepted: 2008-11-06
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Corresponding Authors:
ZHANG Zhuo-yong
E-mail: gusto2008@vip.sina.com
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