In order to realize the rapid,non-destructive,real-time and high-efficiency detection of corn seedling leaf area,a machine vision-based corn seedling leaf area detection device was designed and built.The detecting device is composed of a frame,a light source device,a jacking rotation system,an image acquisition and analysis system,a detection device control system,and the like.The real-time collection and analysis processing of the top view image and the side view image of the corn seedling were completed by the cooperation of the respective parts,and the corn seedlings leaf area was calculated.The results of the device performance tested with corn seedlings showed that when the device was fully loaded and the moving speed of the camera in the X direction and the Y direction was 830 mm/s and 32 mm/s,respectively.The average running time of the detecting device in the top view mode and the side view mode was 190 s and 355 s,respectively.The total detection time was 545 s,with the average time of single corn seedling of 34 s.The average positioning accuracy of the camera was 92% and 90%,respectively.The positioning accuracy was higher.The Pearson correlation coefficients between the leaf area of the top view,the main view and the left view with the actual leaf area of the corn seedlings were 0.901,0.767 and 0.786,respectively.The leaf area of corn seedlings detected by the device was highly correlated with the actual leaf area.It is indicated that the device can meet the needs of batch detection of the leaf area of corn seedlings.