Impacts of early postpartum behavioral patterns on the fertility and milk production of tropical dairy cows.

Abstract

Background and aim: Early postpartum behavioral patterns are pivotal indicators of dairy cow health, reproductive success, and lactation performance, particularly under the environmental stressors of tropical climates. This study aimed to investigate how these behavioral patterns, as captured by smart biosensor data, influence reproductive outcomes, and milk yield in Holstein Friesian cows, with specific emphasis on parity differences and behavioral clustering.

Materials and methods: A total of 227 Holstein Friesian cows, categorized by parity (primiparous vs. multiparous), were monitored using AfiTag-II accelerometers from 3 days prepartum to 30 days postpartum. Behavioral variables - activity, rest time, rest per bout, and restlessness ratio - were subjected to K-means clustering to identify distinct behavioral profiles. Reproductive performance was analyzed using Cox proportional hazard models, while lactation dynamics were modeled using the Wood function to estimate peak yield, peak time, and persistency.

Results: Three distinct behavioral clusters were identified. Primiparous cows in Cluster 1 showed the highest early postpartum activity (~300 min/day at 5 days in milk [DIM]) and restlessness ratios, while multiparous cows exhibited more stable behavioral profiles. Cox regression suggested that cows in Cluster 0 had a higher, although non-significant, likelihood of estrus onset at 40 DIM (Hazard ratio = 1.44, p = 0.09). Lactation modeling revealed that multiparous cows in Cluster 0 attained the highest cumulative milk yield (4896.6 ± 252.1 kg at 305 DIM), while the single cow in Cluster 2 exhibited an atypical lactation curve with a delayed peak and reduced persistency.

Conclusion: Postpartum behavioral clustering reveals parity-specific lactation and reproductive trajectories in tropical dairy cows. Higher activity and restlessness ratios may delay estrus and compromise milk yield, underscoring the potential of behavioral monitoring for targeted reproductive and nutritional management. Integration of sensor-based clustering with routine herd monitoring may support early identification of cows at risk of suboptimal performance, improving reproductive efficiency and milk production in tropical dairy systems.