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Quantitative analysis based on spectral shape deformation: A review of the theory and its applications
Author(s) -
Chen ZengPing,
Xiong Shun,
Zuo Qi,
Shi CaiXia
Publication year - 2018
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.2913
Subject(s) - calibration , chemometrics , computer science , multiplicative function , spectral space , analyte , biological system , mathematics , chemistry , machine learning , statistics , mathematical analysis , biology , pure mathematics
Most of the commonly used calibration methods in quantitative spectroscopic analysis are established or derived from the assumption of a linear relationship between the concentrations of the analytes of interest and corresponding absolute spectral intensities. They are not applicable for heterogeneous samples where the potential uncontrolled variations in optical path length due to the changes in samples' physical properties undermine the basic assumption behind them. About a decade ago, a unique calibration strategy was proposed to extract chemical information from spectral data contaminated with multiplicative light scattering effects. From then on, this calibration strategy has been attentively examined, modified, and used by its developers. After more than 10 years of development, some important features of the calibration strategy have been identified. It has been proved that the calibration strategy can solve many complex problems in quantitative spectroscopic analysis. But, because of the relatively low awareness of the calibration strategy among chemometrics society, its potential has not been fully exploited yet. This paper reviews the theory of the calibration strategy and its applications with a view to introducing the unique and powerful calibration strategy to a wider audience.