On-line detection of mastitis in dairy herds using artificial neural networks

Abstract

Mastitis, one of the most significant diseases in dairy herds, is a highly complex sequence of events with various biological causes and associated physiological and behavioral effects that occur as bacterial infection progresses. The aim of the research is to develop a model for on-line detection of mastitis for robotic milking stations. The data include milking data collected over a four month time period by robots on four farms and monthly test-day milk data collected by veterinarian for determination of the incidence of clinical mastitis (i.e. healthy cows and sick cows). A major part of work involved data pre-processing that plays an important role in this model