The use of infrared thermography and accelerometers for remote monitoring of dairy cow health and welfare

Publication date: Available online 2 March 2017
Source:Journal of Dairy Science
Author(s): M. Stewart, M.T. Wilson, A.L. Schaefer, F. Huddart, M.A. Sutherland
Increasing reliance on automated systems on-farm has led to a need for remote monitoring of health and welfare. We aimed to validate 2 methods that could be integrated into automated systems currently in use: infrared thermography (IRT) to measure respiration rate (RR), and accelerometers to measure the flinch, step, kick (FSK) response and assessing stress and discomfort. We monitored 22 multiparous, nonlactating, Friesian and Friesian × Jersey cows (average 5.1 yr of age) during a baseline period (2 min), a restraint in a crush (2 min), and then a recovery period after exposure to a startle (2 min). We measured RR with continuous IRT imaging of airflow through the nostrils and by counting flank movements from video and live recordings. We recorded heart rate (HR) and HR variability using HR monitors, and we recorded FSK from continuous video analysis of leg movements and indirectly using accelerometers attached to both hind legs. The FSK response was scored between 1 and 4 based on the height and direction of each leg movement. We observed no change in RR, HR variability, or FSK in response to the startle; however, HR increased briefly by 10 bpm. Bland-Altman plots indicated good agreement between the different methods of measuring RR, with average differences of −0.01 ± 0.87, 0.83 ± 0.57, and 0.37 ± 1.02 breaths/min for video versus live, IRT versus live and IRT versus video, respectively. Acceleration was also highly correlated with FSK scores of ≤3 (R² = 0.96) and ≤2 (R² = 0.89) and moderately correlated with FSK scores of 1 (R² = 0.66) over the 4-min sampling period. The results show that accelerometers can provide an indirect measure of the FSK response, and IRT can be used reliably to measure RR. With further development, both technologies could be integrated into existing systems for remote monitoring of dairy cows' health and welfare on-farm.



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