Taking the red Fuji apples produced in Shandong and Shanxi Provinces as the experimental objects, a classification method for identifying the apples produced in different regions is proposed. Firstly, the near infrared (NIR) spectra of the apples are preprocessed by a wavelet soft-threshold method, removing the noise and redundancy. Then, a Principal Component Analysis (PCA) method is used to reduce the dimension of the NIR data. Secondly, a Fisher Discriminant Analysis (FDA) method is used to further extract the features from the data. Finally, a K_near Neighbor Classification (KNN) method is used for the classification and identification of the apples. The experimental result shows that the proposed method can well realize the nondestructive, fast and accurate classification and identification of the apples produced in different regions. Its identification accuracy is up to 97.5%.