PDF
Full
Outline
The accurate identification of sugarcane stem nodes is of significant value for intelligent seed cutting, planting positioning, optimizing the production management process of sugarcane gardens, and improving yields and economic benefits. However, existing sugarcane stem node detection methods still have shortcomings in terms of performance, model complexity, and real-time performance. In order to effectively solve this problem, this study chose to use the advanced YOLOv8 model to visually detect sugarcane stem nodes in a structured scene. First, a field sugarcane image collection experiment was designed, the collected sugarcane images were manually labeled, and an image training set and a test set were established. Then, the YOLOv8 network was used as the sugarcane stem node detection model to determine the optimal hyperparameter combination and conduct model training. Finally, actual recognition experiments in the field are conducted to verify the effectiveness and efficiency of this method. Experimental results show that the precision, recall, mAP, single-frame inference time and model size of our method on the test set are 0.973, 0.958, 0.974,19.80 ms and 6.30 MB respectively. Compared with the Edgeyolo_S_Coco network and Edgeyolo_Tiny network, the mAP value of the YOLOv8_n network has increased by 1.70% and 1.30% respectively, the single-frame inference time has been reduced by 4.71 ms and 1.50 ms respectively, and the model size has been reduced by 33.70 MB and 17.50 MB respectively. This method has advantages in detection performance and generalization ability, and can effectively meet the requirements for algorithm accuracy and model complexity in outdoor environments, providing solid technical support for sugarcane harvesting and planting in intelligent agricultural production.
PDF
120
64
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
关闭全屏
No. 86 Xueyuan South Road, Haidian District, Beijing
010-62199257
qkjq@cast.org.cn
Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House
