Abstract: Abstract: As one of the most popular nuts produced in China, hickory contains large amounts of protein and a variety of unsaturated fatty acids required for human body. However, hickory is prone to rancidity because of the influence of environmental factors such as light, oxygen, and moisture. Therefore, the detection of hickory quality has a certain practical significance. The oxidation of hickory is often accompanied by changes in odor. As a bionic electronic system, E-nose is pretty suitable for hickory quality detection through the analysis of sample volatile compounds' odor fingerprint information. In order to achieve the rapid detection of hickory oxidation quality with electronic nose, the volatile components and quality of hickory were studied by the experiment of accelerating the oxidation. The changes of volatile compounds in the process of oxidation of hickory were determined with electronic nose, and the relative physical-chemical indices such as peroxide value, acid value, anisidine value and total peroxide value were measured every 5 days. The oxidation degree of hickory samples with different oxidation time could be distinguished through principal component analysis (PCA), linear discriminant analysis (LDA), cluster analysis (CA) and physical-chemical index analysis. The principal component regression (PCR) was used to establish the forecast model of the peroxide value, acid value, anisidine value and total peroxide value. The results showed that the response values of T30/1, P10/1, P10/2, P40/1, T70/2, PA/2 were the largest among the 12 sensors. Each sensor's response signal value was enhanced with the increasing of the oxidation time and stabilized at the end of oxidation. The response of the electronic nose sensors increased obviously with the increasing of peroxide value during the oxidation process. The degree of oxidation of hickory in different oxidation stages could be well distinguished by analysis of PCA, CA, LDA and physical-chemical indices, based on which the oxidation process of hickory could be divided into 3 stages. The oxidation process of hickory could be explained by the theory of lipid automatic oxidation. The linear simulation equation was established by using the PCR to predict the peroxide value, acid value, anisidine value, and total peroxide value, and the R2 value was 0.968, 0.975, 0.985 and 0.980 respectively. The results showed that the relative error of each model was less than 16%. The PCR model had a better prediction effect on the peroxide value, acid value, anisidine value and total peroxide value of hickory with different oxidation time. The results show that it is feasible to use the electronic nose system to detect volatile components and quality of hickory with different oxidation time, which provides the new methods and ways for the rapid detection of hickory storage quality.