Careful monitoring of cows helps to minimize pain and distress during calving, and knowledge of the time of birth is important to ensure timely and adequate uptake of colostrum.. However, direct visual observation is time consuming and continuous presence of an observer during stage two of calving can disturb cows; therefore, to predict precisely the calving time, various methods have been proposed to automatically and remotely measure physiological (body temperature; blood level of oestrone- sulphate, 17 beta oestradiol and progesterone; electrolytes in mammary secretion), physical (relaxion of pelvic ligaments; physical separation of the vulva lips) and behavioural indicators. Restlessness is one key behavioural change occurring when calving is approaching. Video cameras or accelerometers recording behaviour of cows can be integrated in systems using image analysis or locomotive activity to alert the farmer when calving is approaching; however, alerting systems require input of benchmark information about behaviours and changes in behaviours which can be predictive of the time of calving. Eight cows in a calving barn were continuously video-monitored. The recordings of the 24 h before calving were analysed to identify the routine behaviours associated with an imminent birth. In our conditions, the only behaviour that was significantly influenced by the distance from calving was frequency of lying bouts; the average number of lying bouts started to increase (P<0.0001) at 3 h before calving reaching the greatest (P<0.0001) value during the last two hours before calving. Increase in the frequency of lying bouts may be an indicator of restlessness useful to predict approaching calving, but further studies are needed to input benchmark values in automated alerting systems.

Restlessness of dairy cows before calving

Rosanna Falconi;
2017

Abstract

Careful monitoring of cows helps to minimize pain and distress during calving, and knowledge of the time of birth is important to ensure timely and adequate uptake of colostrum.. However, direct visual observation is time consuming and continuous presence of an observer during stage two of calving can disturb cows; therefore, to predict precisely the calving time, various methods have been proposed to automatically and remotely measure physiological (body temperature; blood level of oestrone- sulphate, 17 beta oestradiol and progesterone; electrolytes in mammary secretion), physical (relaxion of pelvic ligaments; physical separation of the vulva lips) and behavioural indicators. Restlessness is one key behavioural change occurring when calving is approaching. Video cameras or accelerometers recording behaviour of cows can be integrated in systems using image analysis or locomotive activity to alert the farmer when calving is approaching; however, alerting systems require input of benchmark information about behaviours and changes in behaviours which can be predictive of the time of calving. Eight cows in a calving barn were continuously video-monitored. The recordings of the 24 h before calving were analysed to identify the routine behaviours associated with an imminent birth. In our conditions, the only behaviour that was significantly influenced by the distance from calving was frequency of lying bouts; the average number of lying bouts started to increase (P<0.0001) at 3 h before calving reaching the greatest (P<0.0001) value during the last two hours before calving. Increase in the frequency of lying bouts may be an indicator of restlessness useful to predict approaching calving, but further studies are needed to input benchmark values in automated alerting systems.
2017
Proceedings of the 7th International Conference on the Assessment of Animal Welfare at Farm and Group level WAFL 2017
235
235
Marisanna Speroni, Gloria Dellavedova, Rosanna Falconi, Andrea Summer
File in questo prodotto:
Eventuali allegati, non sono esposti

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/635230
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact