Rayleigh scattering correction for fluorescence spectroscopy analysis

Abstract

Rayleigh scattering signals, not conforming bilinear and trilinear structure of spectral excitation–emission matrices (EEMs), significantly increases the difficulty of spectral resolution. To eliminate or reduce the interference of Rayleigh scattering, we propose missing data recovery (MDR) coupled with principal component analysis (PCA) or parallel factor analysis (PARAFAC) as a novel strategy for Rayleigh scattering correction and corresponding EEM decomposition. MDR treats the scattering data as missing by weighting them as zeros to remove Rayleigh scattering signals thoroughly. Then, sample signals are dramatically recovery in the scattering missing region during rapid iterative process of PCA or PARAFAC to repair bilinearity and trilinearity of EEMs. For significant Rayleigh scattering leading to severe signal loss, profile constraint on both of excitation and emission spectra following fluorescence spectral laws is further proposed for MDR-PCA and MDR-PARAFAC. It is so as to avoid mathematical reasonable but chemical meaningless solutions. The results reveal MDR-PCA and MDR-PARAFAC enable robust Rayleigh scattering correction and EEM decomposition both for simulated and practical data sets. Without the need of any specific priori knowledge and pretreatment such as wavelength selection, it therefore suggests great potential of the proposed method to be a generalized strategy for robust Rayleigh scattering correction and spectral resolution of EEMs.