Application of the ‘tracking signal’ method to the monitoring of udder health and oestrus in dairy cows

Abstract

Two time series models, namely, the moving average model of lag 14 (MAM) and the tracking signal method (TSM), have been used to detect oestrus and udder health in dairy cows based on activity data and electrical conductivity, respectively. The results show that the use of on-line activity data allowed us to obtain high values of sensitivity and specificity for oestrus detection irrespective of the model used. Regarding udder health, sensitivity and specificity values showed that the number of clinical and subclinical mastitis cases detected was similar for the two models, but the specificity value using TSM resulted in a significantly higher value than MAM. Thus, the TSM method could be considered advantageous because of reduction in the number of false positive in healthy cows. The results show that electrical conductivity data of mixed milk samples are useful to detect both clinical and subclinical mastitis with a good sensitivity, if the milk electrical conductivity on-line is correctly measured.