The goal of this research was to develop a method for noninvasive blood glucose assay. Near-infrared (NIR) spectroscopy and Raman spectroscopy, two more promising techniques compared to other methods, were investigated in two kinds of artificial plasma (AP). Calibration models were generated by performing partial least squares (PLS) regression and optimized individually by considering spectral range, spectral pretreatment methods, and number of model factors. The two spectroscopic models were validated for the determination of glucose, and the results show that the two spectroscopic models established are robust, accurate, and repeatable. Compared to Raman spectroscopy, the performance of NIR spectroscopy was much better, with lower root mean square errors of cross-validation (RMSECV) of 0.128 and 0.094 mg/ml, lower root mean square errors of validation (RMSEP) of 0.061 and 0.046 mg/ml, higher correlation coefficients (<i>R</i>) of 99.15% and 99.55%, and higher residual predictive deviations (RPD) of 10.8 and 15.0 for artificial plasma I and II, respectively.

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