外文摘要：Sunscorch, a common disease in pineapple cultivation, is caused by direct sunlight on the surface of lodging pineapple fruits. To mitigate this issue, pineapple fruits are often bagged or supported with fixing rods. This paper presents the design of an anti -lodging machine, comprising an anti -lodging device and an AGV (Automated Guided Vehicle), and develops a machine vision system to precisely aim the anti -lodging device at the crown buds. The YOLOv5s algorithm is enhanced for detecting crown buds. The improvement of the YOLOv5s algorithm includes the introduction of the attention mechanism CBAM to enhance feature extraction, the addition of BiFPN and GhostNet to strengthen feature fusion and to reduce detection time and computational cost. By transforming pixel coordinates, the relative coordinates between the crown bud and the device are calculated to achieve accurate targeting. The experiments demonstrate that the precision, recall, and map_0.5 of the improved YOLOv5s algorithm are 91.89 %, 92.25 %, 94.01 %, and the detection speed is 15.71 ms/image. The average detection speed is 1.14 ms/image and 9.45 ms/image faster than that of SSD and Faster R -CNN, benefiting from a parameter number only 3/4 and 3/7 of SSD and Faster R -CNN, respectively. The results of contrast experiments indicate that, although the lodging prevention rate of this intelligent anti -lodging method is 4 % lower than the manual binding, its operating speed is 2.7 times faster.
外文关键词：deep learning;Pineapple (Ananas comosus (L.) Merr.);Anti-lodging;Fruit fixing;Improved YOLOv5
作者：Liu, Ying;Liu, Tian Hu;Qiu, Jian;Li, Jia-Yi;Chen, Si Yuan;Lai, Jia-Shang;Mai, Bao-Feng
作者单位：South China Agr Univ
期刊名称：COMPUTERS AND ELECTRONICS IN AGRICULTURE
期刊影响因子：0.0
出版年份：2024
出版刊次：218
原文传递申请：江苏省科技资源（工程技术文献）统筹服务平台