Abstract: In this paper, the electronic nose measurement conditions of different sampling time, sensor cleaning time and sample temperature were optimized, and the optimum condition of electronic nose detection was investigated. The different honey samples with 10%, 20%, 30%, 40% and 50% fructose syrup were tested by electronic nose. The data were analyzed by Principal Component Analysis and Linear Discriminant Analysis to explore the effects of different data processing methods on the qualitative identification ability of electronic nose to adulterated honey. It was found that the electronic nose combined with PCA or LDA could distinguish adulterated honey, and LDA had the potential to realize semi-quantitative identification of honey adulteration concentration. It was concluded that the nondestructive identification of adulterated honey based on electronic nose is feasible and practical.