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 2100 nm to 2400 nm with spectra resolution of 1 nm. 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.
Sheffield University, Sheffield, UK. elp09bm@Sheffield.ac.uk
Bilal
B
Malik
Mohammed
M
Benaissa
D002138:Calibration; D005947:Glucose / Q000032:analysis*; D016018:Least-Squares Analysis; D025341:Principal Component Analysis; D019265:Spectroscopy, Near-Infrared / Q000379:methods*
D005947:Glucose