Citation: ZHANG Jin, YE Shi-Zhu, WU Ai-Jing, LI Bo-Yan, LI Jie, ZHAN You-Guo, PENG Hai-Gen, XU Xing-Yang. Continuous Wavelet Transform Combined with Parametric-Free Calibration Enhancement Framework for Calibration of Time-shift Near-infrared Spectra[J]. Chinese Journal of Analytical Chemistry, ;2022, 50(9): 1391-1398. doi: 10.19756/j.issn.0253-3820.211236 shu

Continuous Wavelet Transform Combined with Parametric-Free Calibration Enhancement Framework for Calibration of Time-shift Near-infrared Spectra

ZHANG Jin ¹ ,
YE Shi-Zhu ² ,
WU Ai-Jing ² ,
LI Bo-Yan ¹ ,
LI Jie ³ ,
ZHAN You-Guo ³ ,
PENG Hai-Gen ⁴ ,
XU Xing-Yang ^3,,

1.
Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health, Guizhou Medical University, Guiyang 550025, China;
2.
Technology Centre, China Tobacco Guizhou Industrial Co., Ltd, Guiyang 550009, China;
3.
Yunnan Tobacco Company Kunming Branch, Kunming 650051, China;
4.
Sichuan Vespec Technology Co. Ltd., Chengdu 610041, China

Corresponding author: XU Xing-Yang, yy_xxy@sina.com
Received Date: 20 March 2021
Revised Date: 11 April 2022

Fund Project: Supported by the National Natural Science Foundation of China (No.22004022), the Guizhou Provincial Science and Technology Projects (No.ZK[2021]045) and the Department of Education of Guizhou Province of China (No.KY[2021]163).

Near-infrared (NIR) spectroscopy is a highly efficient and non-destructive technology applied in many areas. The measured spectra, however, are susceptible to shift due to various external interferences, resulting in biased analytical results. Time-shifts in NIR spectra are typical phenomena of continuously shifting spectra with measuring time, which is common in practical applications. In this study,a new method for modeling the time-shift NIR spectra was proposed, in which the shifting signal was divided into shifting background and sample-dependent shifts, and then corrected by continuous wavelet transform (CWT) and semi-supervised parameter-free calibration enhancement (SS-PFCE), respectively. The efficiency of the method was evaluated by modeling 1941 time-shift NIR spectra of soil samples collected in Yunnan Province (China) in 2019 and 2020 to predict the soil organic matter (SOM) content. The spectra taken in 2019 were calibrated (Root mean squared error of prediction (RMSEP)=6.7 g/kg, R²=0.76) and a large deviation was observed in predicting the spectra taken in 2020 (RMSEP=31.3 g/kg, R²=0.50). After CWT treatment, the prediction of spectra measured in 2020 was significantly promoted by predicting the spectra (RMSEP=11.6 g/kg, R²=0.66), and the prediction was further improved by SS-PFCE (RMSEP=8.3 g/kg, R²=0.67). The results indicated that CWT and SS-PFCE were efficient for eliminating the shifting background and sample-related shifts in time-shift NIR spectra, respectively.
- Near-infrared spectroscopy,
- Time-shift,
- Semi-supervised parameter-free calibration enhancement,
- Soil organic matter
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