Detection and Classification of Damaged Potatoes Using YOLO11

Post-harvest sorting of potatoes is a key step in ensuring quality, preventing degradation of stored stocks and reducing subsequent losses. Traditional manual sorting methods are laborious, subjective and inconsistent, especially in large operations. This study presents an approach to potato detection and classification using the YOLOv11 “You only look once” architecture. The application is in a conveyor sorting table environment for post-processing. Two custom datasets were created for clean, w