Computer-based analysis of sow herd performance

Abstract

Increased herd sizes and narrowed income margins are common characteristics of modern swine farming. Therefore good management is becoming more and more important for the economic results. The paper describes a computer-based weak-point analysis of individual sow herd performance. Three stages were distinguished: (1) Tracing deviations between farm performance and a given standard in order to detect trends in the production process. It was shown that modified exponentially weighted moving average control charts are an effective tool in detecting small performances shifts. (2) Weighting the deviations by calculating the statistical and economic relevance allows the ranking of different traits independent of scales and units. (3) Finding the causes for the performance shifts. Decision tree algorithm was investigated to gain more insight in the critical points of production. A decision tree starts with the root node representing the traits which mostly influenced the target attribute (critical point), followed by internal nodes. The generated graphical decision trees are transparent and the outputs are easy to interpret for the farm manager or the consultant. Methods were applied to simulated and real sow herd datasets.