Tail biting is a multifactorial problem with important welfare as well as economic consequences. Different stakeholders in the pig production chain, such as farmers, consumers and policy makers are interested in reducing the level of tail biting, because tail biting may affect productivity, profit and animal welfare. To help assess the expected level of tail biting under specific husbandry conditions we constructed a computer-based decision support system called PIGTAIL, which is a relational database containing a tail biting model based on 133 statements derived from 61 scientific publications. A formalised procedure previously used for modelling animal welfare was used to construct the model. PIGTAIL contains 28 attributes that describe factors that have been associated in scientific research with different levels of tail biting in different housing conditions. Such factors include the provision of substrate, the docking of tails, sex and breed as well as feeding-, health- and climate-related factors. PIGTAIL takes a description of a housing and management system as input and produces a score for the overall risk of tail biting as output. This is a weighted average attribute score, where weighting factors are derived from different measures of tail biting performance, such as tail biting behaviour and tail wounds. The decision support system clarifies the reasoning steps involved in tail biting risk assessment and allows upgrading when new scientific information about tail biting becomes available.
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