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Citation: WANG Li, SHAO Li-Min. Influence of Baseline on Target Factor Analysis Results of Fourier Transform Infrared Spectroscopy[J]. Chinese Journal of Analytical Chemistry, ;2021, 49(3): 474-481. doi: 10.19756/j.issn.0253-3820.201615 shu

Influence of Baseline on Target Factor Analysis Results of Fourier Transform Infrared Spectroscopy

WANG Li ,
SHAO Li-Min ^,

Department of Chemistry, University of Science and Technology of China, Hefei 230026, China

Corresponding author: SHAO Li-Min, lshao@ustc.edu.cn
Received Date: 21 October 2020
Revised Date: 30 December 2020

The successful extraction of target spectra from the experimental data matrix by target factor analysis (TFA) without any preprocessing mainly depends on the concentration variance of the corresponding component. When the variance of ammonia concentrations is low and the baseline drift is serious, TFA may yield false negative results, so baseline correction is applied to improve TFA performance. In this study, six sets of data with different concentration variances and baseline drift were used to compare the baseline removal effects of standard normal variate (SNV), multiplicative scatter correction (MSC), linear fitting, wavelet transform (WT) and adaptive iterative reweighted penalty least squares (airPLS). The results showed that WT could effectively remove the baseline, so that more spectral information of ammonia and methane was allocated in the first eigenvectors of principal component analysis (PCA). The allocated information of ammonia and methane could be successfully extracted by TFA.
- Target factor analysis,
- Principal factor number,
- Baseline correction,
- Wavelet transform
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