Abstract:Chocolates are a popular snack due to their exquisite taste and unique flavor. Nevertheless, instances of chocolate adulteration are on the rise and have recently caught consumer attention, the most common being adulteration with low-cost starch. In this study, near-infrared (NIR) spectroscopy was used for the rapid detection of adulterate sweet potato or potato starch in chocolate. A correction model was established using principal component regression (PCR) and partial least squares (PLS). The effects of spectral range, spectral preprocessing method, and the number of parameters were studied. The result indicated that the highest prediction rate was achieved using PLS for modeling with eight parameters, within a spectral range of 7000 to 4200 cm-1 and first derivative (7 pts) pretreatment. The values for root mean square error of prediction (RMSEP) and the coefficient of determination (Rp2) obtained with this model were 1.7% and 0.9426, respectively. The recovery rates, intraday RSD and interday RSD of samples with varied adulterated proportions were 94.2% to 105.6%, 4.7% to 8.9%, and 5.1% to 11.3%, respectively. The results indicate that NIR spectroscopy can be used as a method to rapidly detect adulterate starch in chocolate.
