Determination of glucose concentration from near-infrared spectra using locally weighted partial least square regression

This paper proposes the use of locally weighted partial least square regression (LW-PLSR) as an alternative multivariate calibration method for the prediction of glucose concentration from NIR spectra. The efficiency of the proposed model is validated in experiments carried out in a non-controlled environment or sample conditions using mixtures composed of glucose, urea and triacetin. The collected data spans the spectral region from 2100nm to 2400nm with spectra resolution of 1nm. The results show that the standard error of prediction (SEP) decreases to 23.85 mg/dL when using LW-PLSR in comparison to the SEP values of 49.40 mg/dL, and 27.56 mg/dL using Principal Component Regression (PCR) and Partial Least Square (PLS) regression respectively.