Abstract
Illegal addition of syrup to honey products would refdeduce the natural nutritional value of honey. It is essential to develop convenient and accurate analytical methods to rapidly monitor products quality. This study investigated the potential usability of combining mid infrared(MIR) and Raman for the quantification of HFGS (high fructose syrup) in bass honey blends. Where in the partial least squares (PLS) model was established to predict the concentration of the adulterant. Three data fusion strategies (low, mid and high-level) were applied to take advantage of the synergistic effect of chemical information from MIR and Raman, and adopted three high-level data fusion strategies to improve the prediction accuracy of the quantitative model. After data fusion, the RMSEP of high-level (1–3) were better than MIR (1.93) and Raman (2.30). Besides, calibration coefficient of determination (R2) and the RMSECV of high-level data fusion (1–3)also outperformed Raman (0.80, 3.38) and MIR (0.95,1.63).Results showed that: (1) The chemical information obtained from MIR and Raman have complementary advantages. (2) The three high-level fusion strategies can be used as a reliable tool for quantitative analysis.
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