Rapid Quantitative Analysis of Corn Starch Adulteration in Konjac Glucomannan by Chemometrics-Assisted FT-NIR Spectroscopy

Konjac glucomannan (KGM) adulterated with cheaper starch cannot easily be identified by visual inspection. This study proposed a rapid and simple method to quantitatively analyze corn starch adulteration in KGM by a Fourier transform near-infrared (FT-NIR) coupled with chemometrics. The partial least-squares (PLS) regression calibration models based on the FT-NIR were designed using 90 samples. Coefficient of determination (R (c) (2)) and root-mean-square error of PLS regression models in calibration set were found to be 0.982-0.990 and 3.596-2.693 % depending on the pretreatments of spectral data, respectively. The other 45 samples were used in the validation (30 samples) and external validation (15 samples) sets. Model 3 (using first derivative with 7 smoothing points) in the validation set yielded satisfactory performance with an R (v) (2) value and root-mean-square error of prediction of 0.989 and 4.890 %, respectively. The overall results indicate that FT-NIR spectroscopy could be a simple and efficient tool for the detection and quantification of the KGM adulterated with corn starch.