Abstract
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.
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Acknowledgments
This work was made possible with funding provided by Doctor Foundation Project of Southwest University (No. SWU112042) and Fundamental Research Funds for the Central Universities (No. XDJK2013B034, No. XDJK2014B019, No. SWU113036), and supported by the Natural Science Foundation of Chongqing (No. cstc2013jcyjA80024).
Conflict of Interest
Jinfeng Zhong declares that he has no conflict of interest. Xiaoli Qin declares that she has no conflict of interest. This article does not contain any studies with human or animal subjects.
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Zhong, J., Qin, X. Rapid Quantitative Analysis of Corn Starch Adulteration in Konjac Glucomannan by Chemometrics-Assisted FT-NIR Spectroscopy. Food Anal. Methods 9, 61–67 (2016). https://doi.org/10.1007/s12161-015-0176-9
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DOI: https://doi.org/10.1007/s12161-015-0176-9