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In order to realize the fast and accurate detection of chicken freshness, an integrated detection device based on electronic nose and vision technology was designed. The structure of the device was divided into three parts, including the control system, the vision system, and the electronic nose system. It simultaneously detected the concentration of gas emitted from chicken samples through the sensor array of the electronic nose, and obtained the visual images of chicken samples by the camera. The gas concentration data were firstly transmitted from the control board to the Jetson Nano board, and then was fused with the visual images for feature extraction and further analysis. Computational fluid dynamics techniques were used to simulate the velocity cloud and velocity vector diagrams of the device under suction conditions to verify the feasibility of gas flow. Based on the gas concentration and image data of chicken samples of different freshness obtained by the device, principal component analysis method was adopted for dimensionality reduction, and chicken freshness grading model was established using support vector machine method with an accuracy rate of 98.7%. The device has the characteristics of high accuracy, portability and stability, which can provide technical support for meat freshness detection.