<scp>YOLOv11n</scp> for precision agriculture: lightweight and efficient detection of guava defects across diverse conditions

These results highlight YOLOv11n's potential for agricultural applications, such as automated defect detection and quality control, which require high accuracy and real-time performance across diverse conditions. This analysis provides insights into deploying YOLO models for agricultural quality assessment to enhance the efficiency and reliability of postharvest management. © 2025 Society of Chemical Industry.