To compare mid-infrared(MIR)and near-infrared(NIR)spectroscopies for the determination of the fat and protein contents in milk,the same sample sets with varying concentrations of fat and protein were measured in the MIR range of 3 200-700 cm-1 and NIR range of 9 000-4 000 cm-1.The spectral features in the two regions were analyzed.The MIR spectra of milk were characteristic due to the MIR inherent molecular specificity,whereas the NIR spectra were relatively characterless due to the NIR low selectivity.Partial least squares(PLS)regression models for fat and protein were developed by using both MIR and NIR spectra.MIR data with no pretreatment gave better results than NIR data.The square correlation coefficient(R2)and the root mean square error of prediction(RMSEP)were 0.98 and 0.10 g/dL for fat and 0.97 and 0.11 g/dL for protein.With NIR techniques,satisfactory results were not obtained with raw data.However,NIR data after pretreatment gave similarly good results to the ones using MIR method.This paper indicates that either of the MIR and NIR spectral methods is reliable for the determination of the fat and protein contents.
In this paper, the propagation characteristics of near-infrared (NIR) light in the palm tissue are analyzed, and the principle and feasibility of using transcutaneous diffuse reflectance spectroscopy for non-invasive blood glucose detection are presented. An optical probe suitable for measuring the diffuse reflectance spectrum of human palm and a non-invasive blood glucose detection system using NIR spectroscopy are designed. Based on this system, oral glucose tolerance tests are performed to measure the blood glucose concentrations of two young healthy volunteers. The partial least square calibration model is then constructed by all individual experimental data. The final result shows that correlation coefficients of the two experiments between the predicted blood glucose concentrations and the reference blood glucose concentrations are 0.9870 and 0.9854, respectively. The root mean square errors of prediction of full cross validation are 0.54 and 0.52 mmol/1, respectively.
