Video-Based Feeding Demand Sensing and Offline Feeding Strategy Evaluation in Group-Housed Pigs: A Single-Pen...

Continuous sensing of group feeding demand is needed to support feeding decisions on large-scale pig farms. In dense group-housing environments, crowding, occlusion, and variation in posture around the trough can reduce the stability of visual feeding-status recognition. Feeding schedules also commonly rely on fixed periods or historical patterns, limiting their ability to assess whether daily feeding-behavior signals are aligned with group demand. Here, we propose a video-based workflow for sensing group feeding activity and conducting an offline replay evaluation of feeding-schedule allocation rules in group-housed pigs. Using synchronized feeding videos and feeder records, we developed a workflow that integrates rotated object detection, visual feeding intensity calculation, time-period-level construction of video-derived feeding demand, and feeding strategy evaluation. Rotated bounding-box detection achieved an mAP50-95 of 0.908 for feeding recognition, supporting its feasibility for feeding/non-feeding recognition in this dense-pen scene. Visual feeding intensity derived from model outputs was most strongly correlated with actual feed intake increment under a 20 min aggregation window with no time lag (r = 0.80). In the evaluation based on video-derived feeding demand, the video-perceived hybrid strategy reduced the peak time difference to 14.51 min, achieved a synchronization correlation of 0.611, and reduced the mismatch rate to 5.13%. These findings suggest that video-based behavioral signals can serve as a group-level proxy for feeding demand and can support offline evaluation of behavior-aware feeding schedules. However, the demand and strategy analyses were based on a single pen observed for 72 h, and validation across additional pens, batches, age stages, seasons, and closed-loop feeding conditions is required before practical deployment.