Abstract: In order to discuss the feasibility of meat adulteration recognition based on electronic nose, an electronic nose was used to analyze yak meat, beef and pork. The response signals were analyzed by principal component analysis (PCA), discriminant factor analysis (DFA) and partial least-squares analysis (PLS). The results indicated that yak meat, beef and pork samples had different characteristic response signals. Electronic nose could recognize yak meat, beef and pork, and also could recognize yak meat and beef samples at different growing locations, but this recognition was not suitable for pork at different growing locations. And it could also identify minced beef added with different ratio of minced pork. Coefficient of determination between sensors response signals and the ratio of minced pork of PLS model was 0.9762. The prediction error of PLS model was within 7.00%. It was proved that electronic nose could be applied in meat recognition.