Using Noseband Sensor Technology to Measure Rumination Time as an Indicator of Feeding and Locomotion Behavior in Dairy Cows
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Date | Start Page | End Page |
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2025-05-07 | 12 | 12 |
Objectives: the aim of this research was to assess rumination time, recorded using innovative technologies, as a parameter for evaluating feeding and locomotion behaviors by measuring chewing rate (chews per minute), eating time, rumination time, drinking gulps, bolus activity, and general activity in dairy cows. Materials and Methods: the study was conducted in West Lithuania from June 1–30, 2023. A total of 434 multiparous Holstein cows (5–30 days post calving, average weight: 550 kg ± 45 kg, producing 12,500 kg energy corrected milk/lactation) were selected from 1,160 clinically assessed cows. Cows were housed in free stall barns with natural and mechanical ventilation and fed a TMR twice daily (06:00, 18:00). Milking occurred at 05:00 and 17:00 using a DeLaval parlor system.The RumiWatch System (RWS) monitored behavior: rumination time (RT) min/h, chews per minute (CPM) n/min, eating chews (EC) n/h, eating time (ET) min/h, drinking gulps (DG) n/ h, bolus (B) n/h, activity (A) min/h, other activity time (OAT) from June 14–30 after a 2-week acclimation phase (June 1–14).Data collection occurred hourly throughout the study. Results: We found a significant negative relationship between RT and OAT (r = -0.435, p < 0.001), as RT increases and OAT decreases. We detected a significant negative relationship between RT and ET (r = -0.544, p < 0.001) as RT increases and ET decreases. A strong, significant negative correlation between RT and EC was also detected (r = -0.508, p < 0.001). We found a strong, significant negative correlation between RT and DG (r = 0.535, p < 0.001). We received a strong, significant positive correlation between RT and B (r = 0.993, p < 0.001). We determined a strong, significant positive correlation between RT and CPM (r = 0.672, p < 0.001). A strong, significant negative correlation between RT and activity was identified (r = 0.488, p < 0.001). Conclusions: overall, this study highlights how new technologies such as the RumiWatch system can enhance our understanding of dairy cow behavior. By studying the relationship between rumination time and different eating and locomotion parameters, we discovered valuable insights into how these behaviors interact. Our results show that as cows spend more time ruminating, they tend to spend less time on other activities, suggesting a clear link between rumination and the cows’ daily activities. connect. Furthermore, the high correlation between rumination time, bolus and chewing rate highlights that rumination is closely related to the general physiology and behavior of dairy cows.