| 光谱学与光谱分析 |
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| Calibration Transfer between Two FTNIR Spectrophotometers Using SVR |
| ZHAO Long-lian1,2,LI Jun-hui1,ZHANG Wen-juan1,WANG Jian-cai1,ZHANG Lu-da3* |
1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100094, China
2. Department of Biomedical Engineering, Medical School of Tsinghua University, Beijing 100084, China
3. College of Science, China Agricultural University, Beijing 100094, China |
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Abstract In the present research，a set of maize powder samples was used to study the calibration transfer between two fourier transform near-infrared (FTNIR) spectrophotometers, and a method of moving window support vector regression machines(SVR) was used to correct the differences between the two instruments. Bruker Vector 22/N was referred to as “master” on which the maize protein calibration model was built. Bruker MPA was referred to as “slave” instrument. A transformation matrix was constructed based on the spectra of a sample set (for calibration transfer) measured on both instruments. After transfer, NIR spectra acquired on “slave” will appear as if they were measured on master instrument. The calibration model available for the master can then be used to predict the transformed spectra measured on the slave. The transfer parameters were computed as follows. For wavelength i, the absorbance vector obtained on the master instrument was regressed against the corresponding absorbance matrix of a spectral window obtained on the slave instrument. Method of SVR was used for regression. Moving the wavelength i and corresponding window, the transfer parameter for each wavelength can be obtained. For the two FTNIR spectrophotometers, a window size of 31 wavelengths and a subset of 15 transfer samples were chosen to establish the SVR regression model between “master” and “slave”. Applying the calibration model to the prediction samples after being corrected by the transfer parameters, a good transfer performance can be achieved. The correlation coefficient (r) is 0.943 4，while the relative standard deviation(RSD) is 4.23%. These results suggest that the SVR method can be used to successfully transfer the calibration model for protein of maize developed on a FTNIR spectrophotometer to another.
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Received: 2007-10-08
Accepted: 2008-01-08
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Corresponding Authors:
ZHANG Lu-da
E-mail: caunir@cau.edu.cn
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