Abstract
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.
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