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Near infrared spectroscopy (NIRS) technology was applied to discriminate the variety of strawberries rapidly. Compared with seven kinds of preprocessing methods, “SNV+MAF+2D” was ascertained as the optimal scheme. Totally 14 characteristic spectrums related to strawberries information were extracted by the correlation coefficient and threshold value method. Three kinds of correction models of PLS—ANN, PLSR and PCR based on wavelength ranging from 548nm to 562nm were established. Verified by the prediction set samples, the optimal correction model was PLS—ANN with nine principal components. Prediction correlation coefficientand root mean square error of prediction(RMSEP) of the PLS—ANN correction model was 0.9677 and 0.461. The results showed that a few characteristic spectrum extracted to establish PLS—ANN correction model would achieve rapid discrimination of strawberries.