Non-linearity correction in NIR absorption spectra by grouping modeling according to the content of analyte

To correct the non-linearity caused by light scattering in quantitative analysis with near infrared absorption spectra, a new modeling analysis method was proposed: grouping modeling according to the content of analyte. In this study, we tested the proposed method for non-invasive detection of human hemoglobin (Hb) based on dynamic spectrum (DS). We compared the prediction performance of the proposed method with non-grouping modeling method. Experimental results showed that the root mean square error of the prediction set (RMSEP) by the proposed method was reduced by 9.96% and relative standard deviation of the prediction set (RSDP) was reduced by 4.73%. The results demonstrated that the proposed method could reduce the effects of non-linearity on the composition analysis by spectroscopy. This research provides a new method for correcting the non-linearity stemming from light scattering. And the proposed method will accelerate the pace of non-invasive detection of blood components into clinical application.