Abstract: A method for the rapid identification of off-flavoured raw pork was investigated in this study as the off-flavoured raw pork often found in slaughtering and quarantine and brought the economic loss to the pork industry. The electronic nose (e-nose) was used to analyse the volatile compounds of normal and off-flavoured pork from two cuts (plum and hind legs) and principal component analysis (PCA), linear discriminant analysis (LDA) and random forest (RF) were combined to identify and classify the pork samples. It was also verified by headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS). The results showed that the PCA, LDA and RF models could effectively differentiate off-flavoured pork from normal pork by using e-nose detection. The test set of hind leg meat showed better classification accuracy than plum meat, which were 91% and 81% respectively. W1S, W5C, W3C, W1C and W2W were the key sensors in the e-nose detection. A total of 50 odour substances were detected by HS-GC-IMS, including 11 ketones, 10 aldehydes, 8 esters, 5 acids, 6 alcohols, 9 other substances (including sulphur and nitrogen containing substances) and 1 uncharacterised substance. Methyl acetate, 2-butanone, 2-hexanone, n-propanol, ethyl isovalerate, and 2-pentylfuran were identified as volatile markers to distinguish between normal and off-flavoured pork screened by using partial least squares discriminant analysis (PLS-DA). The results of the e-nose and HS-GC-IMS measurements were in good agreement, confirming that the e-nose technique could be used for identification and discrimination of off-flavoured raw pork, which would provide a technical reference for the rapid identification of off-flavoured raw pork.