Abstract

The adulteration of roasted green tea by sugar and glucose syrup increases the risk of moisture sensitivity and microbiological hazards in tea products and is considered to be an illegal business operation. The analytical method of high-performance liquid chromatography, which is commonly used for the detection of sugar and glucose syrup, has high specificity and sensitivity, but it is time-consuming and requires highly skilled operators. In this study, near infrared (NIR) spectroscopy combined with multivariate calibration was employed to detect and quantitatively analyse sugar and glucose syrup in roasted green tea. An orthogonal experimental design, sample preprocessing, partial least squares (PLS) models and qualitative models were systemically utilised when developing the method. The model was optimised using leave-one-out cross-validation, and its performance was tested according to root mean square error of prediction and correlation coefficient of determination for the prediction set samples. To reduce heterogeneity, tea samples were ground and homogenised before spectra were acquired. The repeatability of spectra was optimised when the powder particle size was 40–60 mesh, the pressure was 40 MPa and sample cakes had a thickness of 4 mm. PLS models of the sugar and glucose syrup (adulterants) were established under cross-validation and tested with an independent set of samples, yielding coefficients of determination of 0.998, 0.996 and 0.996, 0.998 for sugar and glucose syrup, respectively. The corresponding values for the root mean square error of calibration and prediction were found to be 0.31% and 0.43% for sugar and 0.41% and 0.30% for glucose syrup, respectively. The identification accuracies for these adulterants in roasted green tea were up to 96% and 100%, respectively. These results reveal the feasibility of using NIR spectroscopy for the detection and quantification of adulterants (sugar and glucose syrup) in roasted green tea with acceptable accuracy.

© 2015 The Author(s)

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