Research on an Automatic Seeding Performance Detection and Intelligent Reseeding Device for Leafy Vegetable Plug Seedlings

To address the issues of a low single-seed qualification index and a high missed-seeding index in the process of leafy vegetable plug seedling sowing, this study proposes a lightweight seeding performance detection model named VS-YOLO based on YOLO11n. The model is then deployed on the edge device, the NVIDIA Jetson Xavier NX. A concise and intuitive graphical user interface (GUI) was developed and an automated detection system for vegetable seeding performance was constructed. Based on the empty cells identified by the system, a real-time data transmission mechanism between the Jetson device and a PLC-based control unit is established, enabling the intelligent reseeding device to perform precise reseeding at the designated cell location, achieving row-wise and cell-specific intelligent planting. VS-YOLO incorporates several innovative improvements, including the introduction of a Context Anchor Attention (CAA) module to form the C2PSACAA module, the adoption of the Wise Intersection over Union version 3 (WIoU v3) loss function, and the addition of an extra-small object detection head. These enhancements significantly improve the classification and recognition capability for small-sized vegetable seeds while notably reducing the number of model parameters. Experimental results show that VS-YOLO achieves a mAP@0. 5 of 96. 5% and an F1 Score of 93. 45% in detecting the seeding performance of three types of vegetable seeds, outperforming YOLO11n’s 91. 5% and 85. 19% by 5. 0% and 8. 26%. The parameter count of VS-YOLO is only 1. 61 M, which is 37. 6% lower than YOLO11n’s 2. 58 M, making it lightweight. Operating at a productivity rate of 120 trays per hour, the system achieved an accuracy of 99. 03%, 89. 83%, and 92. 26% for single-seed prediction, multiple-seeding prediction, and missed-seeding prediction. The single-seed qualification index and missed-seeding index were 93. 43% and 4. 68%. After reseeding, these indices improved to 97. 61% and 0. 32%, representing an increase of 4. 18% in the single-seed qualification index and a decrease of 4. 36% in the missed-seeding index. The significant enhancement offers new ideas and technical approaches for the advancement of seeding performance detection and reseeding systems for vegetable plug seedling production.