首页|期刊导航|上海海洋大学学报|基于图像识别的东南太平洋鱿鱼钓钩颜色选择性分析

基于图像识别的东南太平洋鱿鱼钓钩颜色选择性分析OA

Analysis of color selectivity of squid jigs in the Southeast Pacific based on image recognition

中文摘要英文摘要

为掌握茎柔鱼(Dosidicus gigas)对不同颜色钓钩的选择性,以提高钓捕效率,本研究根据"宏润107号"远洋鱿钓船于2025年1-2月在东南太平洋作业期间采集的钓捕视频数据,采用改进的YOLOv8n模型结合ByteTrack多目标跟踪算法,实现了鱿鱼钓钩颜色与鱿鱼上钩行为的自动识别,掌握了茎柔鱼对不同颜色钓钩的选择性及其上钩率.通过优化输入分辨率、调整损失函数及引入数据增强策略,改进的YOLOv8n模型在Box损失上收敛更快,mAP50-95较原模型提升约15%,能够在复杂背景下准确识别鱿鱼钓钩颜色与鱿鱼目标;结合多目标跟踪算法后,系统可实现视频中各鱿鱼钓钩上钩渔获的自动判别.统计结果表明,茎柔鱼对不同颜色钓钩具有明显选择性,其中选择性较高的钓钩颜色依次是黄色、橘色、蓝色、红色、粉色、暗色和浅黄色,但没有显著性差异(P>0.05),而青色与白色钓钩的选择性为最低(P<0.05).研究表明,茎柔鱼对不同颜色钓钩的选择具有一定的偏好性,暖色系钓钩(如黄色、橘色、红色)较能诱发其捕食反应;而冷色系钓钩(如青色、白色)吸引效果较差.本研究基于人工智能图像识别技术实现了远洋鱿钓作业中不同颜色钓钩及其渔获状况的系统量化与全流程自动监测,为鱿钓作业优化、捕捞效率提高提供了技术支撑,同时为构建远洋鱿钓数字孪生系统提供了数据支撑,对推动我国远洋鱿钓渔业的智能化与信息化发展具有重要意义.

The jumbo flying squid(Dosidicus gigas),widely distributed in the southeastern Pacific Ocean,serves as an important target species for China's pelagic fisheries.To understand its selectivity toward different jig colors and improve fishing efficiency,this study analyzed fishing video data collected by the pelagic squid jigging vessel Hongrun 107 during its operations in the southeastern Pacific from January to February 2025.Using an improved YOLOv8n model integrated with the ByteTrack multi-object tracking algorithm,we achieved automatic identification of jig colors and squid hooking behavior,thereby determining the color selectivity and hooking rates of Dosidicus gigas.The results show that by optimizing input resolution,adjusting the loss function,and introducing data augmentation strategies,the improved YOLOv8n model achieves faster convergence in box loss,with the mAP50-95 increased by about 15 percentage points compared to the original model.It can accurately identify squid jigs of different colors and squid targets under complex backgrounds.When combined with a multi-object tracking algorithm,the system can automatically determine which jigs have caught squid in video footage.Statistical results showed that Dosidicus gigas exhibited an obvious selectivity toward jigs of different colors.The jig colors with relatively higher selectivity were yellow,orange,blue,red,pink,dark,and light yellow,in descending order,but the differences were not significant(P>0.05).In contrast,cyan and white jigs showed the lowest selectivity(P<0.05).The study revealed that Dosidicus gigas exhibited a certain preference in its selection of jig colors.Warm-colored jigs(such as yellow,orange,and red)are more effective in eliciting its predatory response,whereas cool-colored jigs(such as cyan and white)show weaker attraction effects.This study demonstrates that AI-based image recognition technology enables systematic quantification and fully automated monitoring of jig colors and catch status in pelagic squid fisheries,providing technical support for optimizing jigging operations and improving fishing efficiency.It also supplies valuable data for building a digital twin system for squid jigging,contributing significantly to the intelligent and digital development of China's pelagic squid fishing industry.

何牧晨;李纲

上海海洋大学 海洋生物资源与管理学院,上海 201306上海海洋大学 海洋生物资源与管理学院,上海 201306||大洋渔业资源可持续开发教育部重点实验室,上海 201306||国家远洋渔业工程技术研究中心,上海 201306||农业农村部大洋渔业可持续利用重点实验室,上海 201306

农业科技

茎柔鱼远洋鱿钓不同颜色钓钩选择性YOLOv8ByteTrack东南太平洋

Dosidicus gigaspelagic squid jiggingjig colorselectivityYOLOv8ByteTrackSoutheastern Pacific

《上海海洋大学学报》 2026 (5)

1215-1224,10

国家重点研发计划(2023YFD2401305)

10.12024/jsou.20251004941

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