Dynamic production monitoring in pig herds III. Modeling and monitoring mortality rate at herd level

• A model for simultaneous modeling of mortality in sows and piglets is presented.
• A multivariate Dynamic Generalized Linear Model (DGLM) is used for first processing.
• Statistical control tools are used in a second step to detect out-of-control cases.
• Variance components are estimated on data from 15 commercial Danish sow herds.
• Correlations of the evolution of mortality are very low between sows and piglets.

Management and monitoring systems may enable the farmers to enhance production results and reduce labor time. The aim of this paper is to develop a dynamic monitoring system for mortality rates of sows and piglets. For this purpose a model for mortality rates is implemented using a Dynamic Generalized Linear Model. Variance components are pre-estimated using an Expectation-Maximization algorithm applied on a dataset containing data from 15 herds, each of them including observations over a period ranging from three to nine years. Data are registrations of events for insemination, farrowing (including stillborn and live born), number of weaned piglets and death of sows. The model provides reliable forecasting on weekly basis. Detection of impaired mortality rate is performed by statistical control tools that give warnings when the mortality (rate) shows sudden or gradual changes. For each herd, mortality rate profile, analysis of model components over time and detection of alarms are computed for two categories, namely sows and piglets.