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.