Using a model of magnesium dynamics in cows to predict the risk of tetany in dairy herds

Abstract

The onset of tetany, when dairy cattle have insufficient magnesium, has a huge impact both economically and on animal welfare. To aid our understanding of the factors that determine magnesium status in dairy cattle, we have adapted and improved a model of magnesium dynamics in sheep. As it stands, this model is of little practical use to a dairy farmer who is primarily concerned with the status of the herd and the risk that animals will contract tetany. In this paper we describe how we have attempted to use the model to give the dairy farmer more useful information. Our approach is to calibrate the model using easily-obtained measurements such as urine and milk magnesium fluxes and then use Monte Carlo simulations in which model parameters are varied randomly according to their statistical distributions. The result of each simulation is classified as the likelihood of tetany occurring based on the value of the simulated magnesium concentration in cerebrospinal fluid. With sufficient simulations we can estimate the risk of tetany for the herd as a whole. A sensitivity measure was used to determine the extent to which each parameter contributes to tetany and hence the importance of knowing its distribution more accurately. Initial results show that our approach has potential. However, the process whereby we use measurements of urinary magnesium flux to calibrate some of the model parameters needs to be improved and a comparison of the calculated risk with actual field data needs to be carried out.