An air-suction substrates removal device was designed to solve the problem of low removal rate in the hole of the plug. Firstly, the missing seedling holes were detected and located by the deep learning model, and then the seedlings were transported to the substrates removal module. The linear module drived the air suction port to above the missing seedling holes. Finally, the negative pressure adsorption method was used to complete the task of removing the substrates. The effects of nine suction port structures were compared and analyzed by using the DEM-CFD coupled simulation method. The results showed that when the diameter of the circular tube at the suction port was 30mm and the height of the shrinking tube was 50mm, the optimal performance of high substrates removal rate and more uniform delivery was exhibited. A test platform for air-suction substrates removal of missing seedling holes was built, and a multi-factor orthogonal test study was carried out. The results showed that the optimal parameter combination was air pressure of 0.5MPa, substrates moisture content of 50%~55%, and air-suction time of 3.0s, with silicone pad. The performance verification test was carried out, and the results showed that the mean average recognition precision was 96.1%, the average positioning success rate was 95.45%, and the average substrates removal rate was over 90%, the working efficiency of the whole machine was 57s/disk, which met the actual requirements of removing seedlings.