This study conducted a comprehensive performance evaluation on YOLO11 and YOLOv8, the latest in the "You Only Look Once" (YOLO) series, focusing on their instance segmentation capabilities for immature green apples in orchard environments. YOLO11n-seg achieved the highest mask precision across all categories with a notable score of 0.831, highlighting its effectiveness in fruit detection. YOLO11m-seg and YOLO11l-seg excelled in non-occluded and occluded fruitlet segmentation with scores of 0.851 and 0.829, respectively. Additionally, YOLO11x-seg led in mask recall for all categories, achieving a score of 0.815, with YOLO11m-seg performing best for non-occluded immature green fruitlets at 0.858 and YOLOv8x-seg leading the occluded category with 0.800. In terms of mean average precision at a 50\% intersection over union (mAP@50), YOLO11m-seg consistently outperformed, registering the highest scores for both box and mask segmentation, at 0.876 and 0.860 for the "All" class and 0.908 and 0.909 for non-occluded immature fruitlets, respectively. YOLO11l-seg and YOLOv8l-seg shared the top box mAP@50 for occluded immature fruitlets at 0.847, while YOLO11m-seg achieved the highest mask mAP@50 of 0.810. Despite the advancements in YOLO11, YOLOv8n surpassed its counterparts in image processing speed, with an impressive inference speed of 3.3 milliseconds, compared to the fastest YOLO11 series model at 4.8 milliseconds, underscoring its suitability for real-time agricultural applications related to complex green fruit environments.

翻译：本研究对"You Only Look Once"（YOLO）系列的最新版本YOLO11与YOLOv8进行了全面的性能评估，重点关注其在果园环境下对未成熟绿色苹果的实例分割能力。YOLO11n-seg在所有类别中取得了最高的掩码精度，达到0.831的显著分数，突显了其在果实检测方面的有效性。YOLO11m-seg和YOLO11l-seg分别在非遮挡与遮挡小果分割中表现优异，分数分别为0.851和0.829。此外，YOLO11x-seg在所有类别的掩码召回率中领先，达到0.815的分数，其中YOLO11m-seg在非遮挡未成熟绿色小果类别中以0.858的分数表现最佳，而YOLOv8x-seg在遮挡类别中以0.800的分数领先。在50%交并比下的平均精度均值（mAP@50）方面，YOLO11m-seg持续表现最优，在边界框和掩码分割上均获得最高分数：在"全部"类别中分别为0.876和0.860，在非遮挡未成熟小果类别中分别为0.908和0.909。YOLO11l-seg和YOLOv8l-seg在遮挡未成熟小果的边界框mAP@50上并列最高，均为0.847，而YOLO11m-seg则取得了最高的掩码mAP@50，为0.810。尽管YOLO11取得了进展，YOLOv8n在图像处理速度上超越了其对应模型，推理速度达到3.3毫秒的优异水平，而最快的YOLO11系列模型为4.8毫秒，这突显了YOLOv8n在涉及复杂绿色果实环境的实时农业应用中的适用性。