Abstract
High-precision spectral data is a necessary prerequisite for quantitative analysis of complex solution components. In order to improve the accuracy of spectral data, this paper proposes a method of synchronous modulation and demodulation. This article also combines the “M + N” theory, cleverly uses the excitation fluorescence of the components in the serum and its self-absorption phenomenon, collects the fluorescence spectrum of the serum sample, and then uses the partial least squares (PLS) method and the cubic optimization model method to establish a model to analyze the urea concentration of serum. At the same time, in order to verify the effectiveness of synchronous modulation and demodulation method, the unmodulated fluorescence spectrum is used to establish the regression model of urea concentration. Compared with the unmodulated fluorescence spectrum modeling results, the fluorescence spectrum modeling results after modulation and demodulation have been significantly improved. In the modeling results of fluorescence spectrum after synchronous modulation and demodulation, the Rc is 0.916753, the RMSEC is 2.05848 mmol/L, the Rp is 0.79663, and the RMSEP is 3.16812 mmol/L, the Rp-all is 0.88879, and the RMSEP-all is 2.32114 mmol/L. The results show that the method of synchronous modulation and demodulation proposed in this paper not only reduces the influence of dark current, ambient light and background noise on the signal-to-noise ratio of the spectral data, but also effectively avoids the error caused by the non-synchronization of the chopper and the spectrometer. Therefore, the method used in this paper not only improves the signal-to-noise ratio and accuracy of spectral data, but also improves the accuracy of spectral quantitative analysis of complex solutions.
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More From: Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy
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