YOLOv11-Pose-Based Tracking Reveals Neuropeptide F Regulation of Agonistic Behavior in Macrobrachium rosenbergii

The giant freshwater prawn Macrobrachium rosenbergii is inherently aggressive, and this innate trait constitutes a major bottleneck restricting high-density intensive aquaculture. In this study, we developed behavioral phenotyping analysis software integrating YOLOv11-pose and the SORT tracking algorithm to automatically recognize and quantify agonistic behaviors. To validate the reliability of this platform, we used it to investigate the role of neuropeptide F (NPF) through loss- and gain-of-function strategies. The platform successfully captured behavioral differences across treatments and generated results that were consistent with manual observations, confirming its accuracy and utility for automated behavioral analysis. Moreover, it provided additional kinematic metrics that are not accessible through manual observation, offering more comprehensive behavioral quantification. Mechanistically, NPF silencing reduced feed intake, suppressed growth, and disrupted hepatopancreatic glycolysis, suggesting that NPF may modulate aggression at least partly through energy metabolic pathways. Collectively, this study provides a robust tool for behavioral phenotyping in crustaceans, with potential applications for behavior-based management in intensive farming systems.