The Effect of Noise in Raman Spectra on the Reconstruction of the Concentration of Amino Acids in the Mixture by Multivariate Curve Resolution (MCR) Analysis

Irina A. Matveeva (Login required)
Samara National Research University, 34 Moskovskoe shosse, Russia

Lyudmila A. Bratchenko
Samara National Research University, 34 Moskovskoe shosse, Russia

Oleg O. Myakinin
Samara National Research University, 34 Moskovskoe shosse, Russia

Elena N. Tupikova
Samara National Research University, 34 Moskovskoe shosse, Russia

Valery P. Zakharov
Samara National Research University, 34 Moskovskoe shosse, Russia


Paper #3424 received 23 May 2021; revised manuscript received 25 Jun 2021; accepted for publication 26 Jun 2021; published online 30 Jun 2021.

DOI: 10.18287/JBPE21.07.020309

Abstract

Changes in the concentration of free amino acids in biological tissues is a sign of impaired protein metabolism in patients with cancer. Recently, Raman spectroscopy has been used for early diagnostics of oncological diseases. The concentrations of individual components of biological tissue (for instance, the concentrations of amino acids) can be obtained by decomposing the tissue Raman spectrum. This study was designed to evaluate the effect of noise in the Raman spectra of individual amino acids on the result of the decomposition of the spectra of an amino acid mixture. As a decomposition method, we used Multivariate Curve Resolution-Alternating Least Squares (MCR–ALS) analysis and investigate experimental Raman spectra of amino acids and mathematically simulated Raman spectra of amino acid mixtures. Noise with different signal-to-noise ratios (SNR) was artificially added to both the experimental spectra of pure amino acids and the spectra of the mixtures. Concentration values for each amino acid obtained as a result of applying the MCR–ALS analysis have been compared with the corresponding true values and the correlation coefficients have been calculated. The results show a less pronounced negative effect of noise in the case when the spectra of pure amino acids (which were used as a basis for the MCR–ALS analysis) are noisy, and a more pronounced negative effect when the spectrum of the mixture is noisy. The accuracy of reconstruction of an amino acid is also negatively affected by strong background fluorescence in the amino acid spectrum. Moreover, the results indicate that using the basis spectra with a high SNR (SNR = 5) makes it possible to successfully estimate the amino acid concentrations in a mixture even when the Raman spectrum of the mixture is noisy and has a low SNR (SNR < 5).

Keywords

Signal-to-noise ratio; Raman spectrum; Raman scattering; multivariate curve resolution; free amino acids

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