Detection of Estrus and Mastitis: Field Performance of a Model

A new detection model (IMAG model) for estrus and mastitis in dairy cows was tested on four farms during severalyears. Such a test is necessary because information is lacking about the performance of detection models under fieldconditions. The test gave insight into the field performance of the IMAG model and the results were compared with the resultsof older models and with the results predicted by experts. Sensor data of milk yield, milk temperature, electrical conductivityof milk and animal activity were the inputs for the IMAG model. The IMAG model is based on time series analysis combinedwith a Kalman filter. This structure yields cowdependent model parameters and combines data of different sensors. Resultswere compared with the manufacturers model (supplied with the sensors), based only on exponential smoothing on data fromone sensor. The sensor equipment differed between farms. The sensitivity (percentage of estruses detected) for estrus variedfrom 63 to 80%, depending on the threshold used. Specificity (nonestruses not detected as estrus) varied from 94 to 98%.The sensitivity for clinical mastitis varied from 55 to 80%, depending on the threshold used. The specificity for mastitis variedfrom 94 to 99%. Significant differences existed between farms, in sensitivity for estrus and mastitis. The applied equipmentcould only partially explain the differences in estrus and mastitis detection results between farms. No relation between stageof lactation and activity level was found, although a lower activity level in the first period of lactation might be expected.The main conclusion is that a detection model can give good results, but only if the equipment is working properly. The newmodel outperformed the manufacturers model.