Use of computer vision to automatically identify behaviours of healthy and disease-challenged male broiler chickens

Automated behavioral monitoring may offer opportunities to assess health in broiler chickens. This study aimed to (i) evaluate behavioral changes following challenge with Eimeria spp. and infectious bronchitis virus (IBV) combined with avian pathogenic Escherichia coli (APEC), and (ii) characterize patterns across age and time of the day. Across four rounds, 132 Ross 308 broilers were assigned to three groups (control, Eimeria, and IBV+APEC), with four replicate pens of 11 birds each. Challenges were applied on day 14 (Eimeria), day 21 (IBV), and day 24 (APEC). A total of 12 behaviors were quantified from 10-min video recordings collected every 2 h between 07:00 and 21:00 from days 14 to 41, divided into four periods: Period 1 (d14–20), Period 2 (d21–27), Period 3 (d28–34), and Period 4 (d35–41). Behavior was primarily driven by age. In control birds, locomotion and exploratory/foraging decreased progressively, while sleeping increased; inactivity remained stable. Time-of-day analysis revealed diurnal patterns with higher afternoon/evening activity and lower sleeping in these periods compared with morning. Relative to controls, Eimeria-infected birds showed variable drinking and sustained increased locomotion and exploratory behavior (periods 1–4), representing a non-classical response to intestinal challenge. IBV+APEC-challenged birds exhibited modest changes: decreased inactivity (period 2) and increased panting (period 4), with largely unchanged activity patterns. Disease challenge altered diurnal patterns, with disease-specific effects on circadian-dependent behaviors. These findings highlight the importance of age-specific baselines and the potential of time-of-day-dependent behavioral analyses and circadian markers for detecting disease-related deviations and enabling early disease detection through automated behavioral monitoring.