Citation: LI Zhi-Gang, PENG Si-Long, YANG Ni, WANG Qiao-Yun, LV Jiang-Tao, HU Xiao-Fei. Quantitative Analysis Method of Infrared Spectra Based on Derivative Spectra Fusion Modeling[J]. Chinese Journal of Analytical Chemistry, ;2016, 44(3): 437-443. doi: 10.11895/j.issn.0253-3820.150765 shu

Quantitative Analysis Method of Infrared Spectra Based on Derivative Spectra Fusion Modeling

1.
¹ College of Information Science and Engineering, Northeastern University, Shenyang 110819, China;
2.
² Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China;
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³ Shanghai Institute of Measurement and Testing Technology, Shanghai 201203, China

Corresponding author: LI Zhi-Gang,
Received Date: 28 September 2015
Available Online: 15 December 2015
Fund Project: 本文系国家自然科学基金(No.11404054) (No.11404054)河北省自然科学基金项目(No.F2016501138,F2014501127)资助 (No.F2016501138,F2014501127)

A derivative spectral estimator (DSE) based on singular perturbation technique was designed and a quantitative analysis method based on derivative spectra information space, termed derivative spectra fusion interval partial least squares (DSF-iPLS) modeling was proposed. DSF-iPLS mainly focused on obtaining final fusion model by making full use of derivative spectra information. The glucose spectra dataset with concentrate ranging from 0.04% to 5% and the beer spectra dataset with the original extract concentration ranging from 4.23 to18.76°P (Plato) were used to evaluate the effectiveness of the proposed quantitative analysis method. The experiment results indicated that DSF-iPLS model for two infrared spectra datasets provided the minimum root mean square error of prediction (RMSEP) and the values were 0.121 and 0.087, respectively. Compared with other single model, DSF-iPLS model based derivative spectra could provide more excellent predictive performance.
- Quantitative analysis,
- Singular perturbation technique,
- Derivative spectra,
- Interval partial least squares,
- Fusion modeling
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沈阳化工大学材料科学与工程学院沈阳 110142