The influence of spectral characteristics on the accuracy of concentration quantitatively analysis by near infrared spectroscopy

In order to solve the problem of measurement blindness caused by the lack of detectability analysis in the near-infrared spectroscopy (NIRS), two important parameters including Equivalent Signal Noise Ratio (ESNR) and Overlapping Coefficient (OC) are proposed in this manuscript. According to the proportion of the component absorbance to the total absorbance and the overlap degree between near-infrared spectral curves of the components, the above parameters can achieve quantitative analysis of the concentration of components tested based on NIRS. The research combines the theoretical simulations and ethanol concentration experiments. The quantitative relationship between above two parameters and spectral analysis error is discussed by the partial least squares (PLS) modeling NIRS. The estimated RMSE of ethanol concentration obtained by theoretical analysis of this study was 0.30%, and the actual RMSE of near-infrared spectroscopy was 0.32%. The relative error is 6.67%, and the results are consistent. This study provided an effective and rapid prediction method for the quantitative analysis of NIRS, and optimized the theory of the detectability analysis of NIRS, which is a significant guidance for the quantitative analysis of the concentration measured by NIRS.