Abstract: To improve of tobacco transplanting operations quality and optimize transplanting work, a tobacco transplanting recognition system based on improved YOLOv8 was proposed．Firstly, software and hardware design of tobacco seedling removal, picking, and transplanting device overall structure was designed．Key mechanisms such as conveying mechanism, information collection mechanism, and seedling picking and transplanting mechanism were analyzed for their operational principles and component selection．Then, a tobacco transplanting recognition method based on YOLOv8s-MS-DCNv2-ILOSS（YOLOv8s-MSDI）was proposed to achieve accurate recognition of smaller targets．Finally, this method was applied into system to complete automatic tobacco transplanting operations．Results showed that YOLOv8s-MSDI model had an average accuracy across all classes of 98.03% and an F1 value of 99.45% in tobacco seedling recognition tasks, which were higher than those of YOLOv3-FDN, YOLOv5s, and Faster R-CNN．This analysis showed that YOLOv8s-MSDI improved accurate extraction and recognition of tobacco seedling characteristics, thereby reducing missed detection rate, improving tobacco transplanting quality and efficiency, and further enhancing tobacco transplantation operations informatization level．