Abstract：The robust NIRS model must be developed by the representative samples and precise chemical values, taking much of work. To reduce the calibration work, the present paper explored the NIRS model developed using ethanol liquor to predict ethanol of the wine samples. The authors used the gene arithmetic (GA) method to select the calibration region(2 245-2 320 nm)which has relatively high correlation with the consistency of ethanol in ethanol liquor and has little interfere by other components in wine. To remove the systematic error between the calibration set of ethanol liquor and the prediction set of turbid vinous ferment liquid, according to the method of slope/bias, the authors selected 21 samples in prediction set which can represent the range of consistency of vinous ferment liquid to revise the ethanol model in order to predict the remaining wine samples well. After the calculation, the authors obtained the bias and the slope to be 0.523 3 and 0.980 8, respectively. Then we predicted the other turbid samples of wine using the ethanol liquor model after being revised by the slope/bias method. And the prediction model for the ethanol of turbid samples was developed, with r, RPD and RSD for the prediction model for ethanol of samples being 0.99%, 11.71% and 3.11%, respectively, indicating that the ethanol liquor model is robust and can serve as the model of vinous ferment liquid to detect the ethanol of the wine. So this method can largely reduce the calibration work during the NIR calibration process, and has the practical feasibility and application value.
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