Study on the Development of the Standardization of Near-Infrared Spectra
Date Issued
2006
Date
2006
Author(s)
Wu, Chi-Hsiang
DOI
zh-TW
Abstract
This research used PDS (Piecewise Direct Standardization), DPDS (Differential Piecewise Direct Standardization) and SVS (Support Vector Standardization) to standardize spectra, which were obtained by using different instruments. Among them, PDS and DPDS are linear standardization methods based on PLSR (Partial Least Square Regression), while SVS is a nonlinear standardization method based on SVR (Support Vector Regression). Besides, to improve the use of standardized spectra on established database and models, Model Adaptation was introduced with samples were selected by KS (Kennard-Stone algorithm). The mixture of sucrose and NaCl was used as samples in this study, in which the content of sucrose was served as the reference data. Three models of PDS, DPDS and SVS were adopted to investigate the spectra standardization for the cases of different time, attachments and instruments. The results indicated that SVS was the best model. Regarding the effect of measurements at different time, spectra error SEPw was 0.044 after standardization, and standard refrence value error SEPc was 6.464 after Model Adaptation. Regarding the measurements by using different attachments on the same instrument, SEPw and SEPc were 0.050 and 12.911 respectively after standardization, and SEPc was 6.471 after Model Adaptation. As of the measurements by using different instruments (Online 6500 and NIRS 6500), SEPw and SEPc were 0.040 and 8.842 respectively after standardization, and SEPc was 7.318 after Model Adaptation. As of the measurements by using different instruments (N-400 and NIRS 6500), spectra error SEPw was 0.042 after standardization, and standard refrence value error SEPc was 5.623 after Model Adaptation. As of the measurements by using different instruments (N-400 and Online 6500), spectra error SEPw was 0.034 after standardization, and standard refrence value error SEPc was 6.03 after Model Adaptation; however, if same wavelength range (1100~2000nm) was selected, standard error of spectra SEPw was 0.02 and SEPc was 7.800 without Model Adaptation. In this study, the investigation was also conducted by exchanging the relation of Master and Slave in the standardization. The results revealed that when a less precise instrument was standardized to a more precise instrument, both SEPw and SEPc increased. After exchanging of Online 6500 and NIRS 6500, SEPw and SEPc were 0.072 and 15.338 respectively after standardization; if same wavelength range (1100~2000nm) was selected, standard error of spectra SEPw was 0.016 and SEPc was 12.470. Spectra standardization methods with Model Adaptation were successfully developed in this study, it allowed to transfer spectra among different attachments and instruments, and to reduce the spectra difference due to different measurement time.
Subjects
標準化
近紅外光
多變數迴歸分析
支援向量迴歸
Standardization
Near Infrared
Multivariate Analysis
Support Vector Regression
Type
thesis
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