Quantifying characteristics of information-technology applications based on expert knowledge for detection of oestrus and mastitis in dairy cows.

Expert opinions were elicited about the characteristics at the commercial-farm level of on-line information technology (IT) applications that are able to detect oestrus and mastitis in dairy cows. Since actual data of these characteristics are not available, judgmental data provided an alternative means to interpret the implications of research results for commercial farms. Applications included were activity measurement, milk-production measurement, electrical conductivity of quarter milk, automated concentrate feeders and milk-temperature measurement. Sensitivity and specificity of detection of oestrus (OD), clinical-mastitis (CMD) and subclinical-mastitis (SCMD) were ascertained. Conjoint-analysis was used to assess the effect of each application indirectly by decomposing the evaluated overall detection characteristics of a predefined number of IT combinations. The individual experts were consistent in evaluating the alternatives, but there was variation in estimates among experts. Estimations of the main effects of the applications and important first-order interactions were incorporated into the detection models. Implementation of all applications under study resulted in overall sensitivities and specificities of 82% and 90%, 73% and 87%, 58% and 82% for OD, CMD and SCMD, respectively. Further research is necessary that should take into account costs and benefits of the different detection systems based on the current status of farm performance (e.g. OD and mastitis incidence) and farm structure (e.g. farm size, years in operation of the milking parlour and parlour layout). Research to do this is currently in progress.