Association of production diseases with motor activity-sensing devices and milk progesterone concentrations in dairy cows

We have previously established that the efficiency of identifying oestrus with activity-sensing devices can be compromised by common production diseases; the present study was undertaken to determine how these diseases may affect device readings. A total of 67 Holstein-Friesian cows, >20 days postpartum, were equipped with activity-sensing neck collars and pedometers, and simultaneous milk progesterone profiles were also monitored twice a week. The influences of common production stressors on maximum activity and progesterone values were analysed. Approximately 30% potential oestrus events (low progesterone value between two high values) remained unrecognised by both activity methods, and progesterone values in these animals were higher on the potential day of oestrus when both activity methods did not detect an event (0.043 ± 0.004 versus 0.029 ± 0.004 ng/mL; P = 0.03). Data from a subset of 45 cows (two events each) were subjected to mixed models and multiple regression modelling to investigate associations with production diseases. Cow motor activity was lower in lame cows. Maximum progesterone concentrations prior to oestrus increased as time postpartum and body condition score (BCS) increased. There were also fewer days of low progesterone prior to oestrus associated with increases in BCS and maximum progesterone concentrations prior to oestrus. In conclusion, lameness was associated with lower activity values, but this suppression was insufficient to account for lowered oestrus detection efficiency of either device. However, associations were identified between production diseases and progesterone profiles. •Production diseases (especially lameness, low BCS) affect maximum motor activity.•The impact was insufficient to influence the efficient identification of oestrus.•Several milk progesterone indices were related to the display of oestrus.•Associations were identified between production diseases and progesterone indices.