Quantitative Raman Spectroscopy when the Signal-to-Noise is Below the Limit of Quantitation due to Fluorescence Interference: Advantages of a Moving Window Sequentially Shifted Excitation Approach

Abstract

Raman spectroscopy is a useful analytical tool. However, its application is often limited because shot noise from fluorescence obscures the Raman signal. In such cases, quantitative analysis is not possible when the signal-to-noise ratio (SNR) drops below two. A method is described for performing quantitative Raman spectroscopy that not only removes fluorescence backgrounds, but also results in a significant improvement in the SNR. The Raman data is extracted using a moving window sequentially shifted excitation algorithm. To demonstrate the capabilities of the method, a binary mixture of two analytes at varying concentrations is quantified in the presence of a highly fluorescent dye. Linear calibration plots were constructed and validated for the binary model using individual Raman peaks with SNR ranging from 0.073-12.6; r(2) values are greater than 0.96 in all cases, with all but the weakest peaks yielding values greater than 0.997. The presented method demonstrates a universal and autonomous approach for the quantitative analysis of highly fluorescent samples via Raman spectroscopy. The lower limit on the SNR ratio for quantitative Raman analysis with the described method is 0.1. In order to assess the effectiveness of the presented method, the entire set of experiments was also processed using the more common shifted excitation Raman difference spectroscopy (SERDS) approach. The advantages of the proposed method over SERDS are demonstrated for both the detection limit and the SNR of the processed spectra.

Glucose monitoring and adaptive feeding of mammalian cell culture in the presence of strong autofluorescence by near infrared Raman spectroscopy

“…Autofluorescence dominates the spectrum for the RXN785. The impact of autofluorescence is more than just an undesirable background; increased autofluorescence also increases the noise floor through shot noise . Processing the spectrum with common algorithms to remove backgrounds, such as fitting and subtracting a polynomial, yield a noisy Raman spectrum (Figure B).…”

Raman spectroscopic detection of interleukin-10 and angiotensin converting enzyme

“…In addition, for low concentration samples, the SNR might below the limit of quantitation due to the fluorescence interference. A technique was proposed which requires a wavelength tunable laser for sequentially shifting of excitation wavelength [11], however, having a fixed wavelength excitation laser, we were unable to use this approach. An alternative approach is to use peak intensity ratios of each compound to identify each compound independently and quantify its concentration.…”

“…However, to reach the pg/mL detection limit, sample preparation is complicated and time consuming [5]. Other techniques for cytokines detection and quantification can reach such concentrations, like surface enhanced Raman spectroscopy (SERS) [6][7][8][9][10], high performance liquid chromatography (HPLC) [11], pyro-concentrator (PC) [12,13], mass spectrometry (MS) [14] etc.. Although the sensitivity of these techniques is comparable or higher than methods using immunoassays, they all need a biopsy to acquire the sample invasively and test in vitro.…”

New qualitative analysis strategy for illicit drugs using Raman spectroscopy and characteristic peaks method

“…The second one is the use of a longer laser excitation wavelength, such as the use of 1,064‐nm excitation spectrometer 15,16 . The third one is the use of shifted excitation method 14 or improved moving window sequentially shifted excitation (SSE) approach 17 to extract the Raman data from different spectra. The last one is the use of surface‐enhanced Raman spectroscopy (SERS), which can enhance the Raman signal and reduce interference simultaneously 18,19 .…”