A new strategy for quantitative analysis of a major clinical biochemical indicator called glycatedhemoglobin(Hb·A1c)was proposed.The technique was based on the simultaneous near-infrared(NIR)spectral determination of hemoglobin(Hb)and absolute HbAlc content(Hb·HbA1c)inhuman hemolysate samples.Wavelength selections were accomplished using the improvedmoving window partial least square(MWPLS)method for stability.Each model was establishedusing an approach based on randomness,similarity,and stability to obtain objective,stable,andpractical models.The optimal wavebands obtained using MWPLS were 958 to 1036 nm for Hband 1492 to 1858 nm for Hb·HbA1c,which were within the NIR overtone region.The validationroot mean square error and validation correlation coeficients of prediction(V-SEP,V-Rp)were 3.4g L^(-1) and 0.967 for Hb,respectively,whereas the corresponding values for Hb.HbAic were 0.63 g L^(-1) and 0.913.The corresponding V-SEP and V-Rp were 0.40% and 0.829 for the relativepercentage of HbA1c.The experimental results confirm the feasibility for the quantification of HbAlc based on simultaneous NIR spectroscopic analyses of Hb and Hb·HbA1c.
Alcohol,total sugar,total acid,and total phenol contents are the main indicators of wine quality detection.This study aims to establish simultaneous analysis models for the four indicators through near-infrared(NIR)spectroscopy with wavelength optimization.A Norris derivative filter(NDF)platform with multiparameter optimization was established for spectral pretreatment.The optimal parameters(i.e.,derivative order,number of smoothing points,and number of differential gaps)were(2,9,3)for alcohol,(1,19,5)for total sugar,(1,17,11)for total acid,and(1,1,1)for total phenol.The equidistant combinationpartial least squares(EC-PLS)was used for large-scale wavelength screening.The wavelength step-by-step phaseout PLS(WSP-PLS)and exhaustive methods were used for secondary optimization.The final optimization models for the four indicators included 7,10,15,and 13 wavelengths located in the overtone or combination regions,respectively.In an independent validation,the root mean square errors,correlation coefficient for prediction(i.e.,SEP and RP),and ratio of performance-to-deviation(RPD)were 0.41 v/v,0.947,and 3.2 for alcohol;1.48 g/L,0.992,and 6.8 for total sugar;0.68 g/L,0.981,and5.1 for total acid;and 0.181 g/L,0.948,and 2.9 for total phenol.The results indicate high correlation,low error,and good overall prediction performance.Consequently,the established reagent-free NIR analytical models are important in the rapid and real-time quality detection of the wine fermentation process and finished products.The proposed wavelength models provide a valuable reference for designing small dedicated instruments.
