A Modified Least-Squares Method for Quantitative Analysis in Raman Spectroscopy

Quantitative spectral analysis is highly demanded in many applications such as pharmaceutical research, biological sample analysis, and food quality control, in which Raman spectroscopy has been established as a label-free analytical tool. In an attempt to address the challenge faced by the classical least-squares method during the quantification of analyte concentrations, which is induced by potential inaccuracy or variations in the spectral library, we propose a modified least-squares method that accounts for such variations as individual Gaussian functions with variable parameters. Both the spectral library and the analyte concentrations are updated during iterations. The method is validated on both simulated data with multiple Gaussian peaks and experimental measurements from phantoms of chemical mixtures and K562 leukemia cells.