A dataset to study group-housed sows’ individual behaviours and production responses to different short-term events

Abstract

The relational database SOWELL was created to better understand the behaviour and individual responses of gestating sows facing different short-term events induced: a competitive situation for feed, hot and cold thermal conditions, a sound event, an enrichment (straw, ropes and bags available) and an impoverishment (no straw, no objects) of the pen. The data were collected on 102 crossbred sows equipped with activity sensors, group-housed in video-recorded pens (16–18 sows per pen), with access to automatons. Feeding and drinking behaviours were extracted from the electronic feeders and drinkers’ recordings. Social behaviours, physical activities and locations in the pen were recorded thanks to manual video analysis labelling at the individual scale. Accelerometer fixed on the sows’ ears also recorded individual physical activities. The physical activity was also determined at a group scale by automatic video analysis using deep learning techniques. BWs, back fat thickness, and body condition (cleanliness, body damages) were recorded weekly during the whole gestation. Last gestation room data regarding environmental conditions (temperature, humidity, noise level) were recorded using automatic sensors. The database can fulfil different research purposes, namely sows’ nutrition for example to better calculate the energy requirements regarding environmental factors, or also on welfare or health during gestation by providing indicators.