Maciej Oczak

How do pigs behave before starting an aggressive interaction? Identification of typical body positions in the early stage of aggression using video labelling techniques.

The aim of this study was to identify, quantify, and describe pre-signs of aggression in pigs and the early stages of aggressive interactions. The experiment was carried out at a commercial farm on a group of 11 male pigs weighing on average 23 kg and kept in a pen of4 m x 2.5 m. In total 8 hours were videorecorded during the first 3 days after mixing. As a result, 177 aggressive interactions were identified and labelled to find pre-sign body positions before aggressive interactions, attack positions and aggressive acts performed from these positions. A total of 12 positions were classified as pre-signs (P1-P12) and 7 of them were identified immediately at the start of aggressive interactions (P6-P12). Most common pre-sign positions were P3-pigs approaching and facing each other (24%) and P2-initiator pigs approaching from the lateral side (18%). In 80% of the cases the duration of pre-signs was 1-2 sec 72% of all aggressive interactions were short (1 to 10 sec). The most frequent attack positions were P12-inverse parallel (39.5%), P7-nose to nose, 90 degrees (19.77%) and P9-nose to head (13.5%). The most frequent aggressive acts from attack positions were head knocking (34.4%), pressing (34.4%) and biting of different body parts (29.4%). Head knocking was mostly observed in relation to P7 and P2 positions and biting was common in the P7 position. In conclusion, pigs adopt specific pre-signs and body positions before the escalation of aggressive interactions. This could be used as potential sign to identify a beginning aggression.

Can an automated labelling method based on accelerometer data replace a human labeller? - Postural profile of farrowing sows

We detect postural behaviour of farrowing sows on the basis of accelerometer data.Postural behaviours detected are active, resting in lateral and sternal positions.We detect postural behaviour of sows with accuracy of 70% in cross-validation.Accuracy is too low to detect the effect of pen type on behaviour of the animals.Accuracy is high enough to detect the effect of crating on behaviour of the animals. The objective of this research was to develop a method for the automated classification of sows postures based on accelerometer data. The second objective was to evaluate if the technique can be used in a reliable way instead of human labelling to automatically create postural profiles of sows. The experiment took place at the research farm of The University of Veterinary Medicine Vienna. The farm had a herd of 120 Large White sows. Data were collected from sows housed in three types of farrowing pens: wing, trapezoid and SWAP (Sow Welfare and Piglet Protection). The behaviour of 18 sows was video recorded and labelled for a period of 24h before the start of farrowing until the end of farrowing. The focus of labelling was on three types of postural behaviours: active, resting in lateral position (RLP) and resting in sternal position (RSP). Each sow had a specific ear tag with a 3 axis accelerometer sensor. Acceleration was measured at a frequency of 10Hz. Linear discriminant analysis (LDA) was used to classify the three labelled postural behaviours on the basis of acceleration data. To evaluate how the LDA classifier would generalise to an independent dataset an 18-fold cross-validation method was used. The overall classification accuracy of postural behaviours with the developed method was 70% in cross-validation and 73% on the training set. Comparison of labelling and classification results revealed that the accuracy is not good enough to detect the effect of pen type on the behaviour of the animals. However, the influence of crating on time spent resting in either a lateral or sternal position was correctly recognised with the automated method. The developed method could be further tested for the automated monitoring of the health and welfare status of sows.

Cognitive Enrichment in Piglet Rearing: An Approach to Enhance Animal Welfare and to Reduce Aggressive Behaviour

It is known that pigs raised in enriched environments express less aggressive behaviour. For this reason, a new method of cognitive environmental enrichment was experimented at the University of Veterinary Medicine Hannover, Germany. In the first phase, 78 suckling piglets were trained to learn the link between a sound given by an electronic feeder and a feed reward in the form of chocolate candies during a period of 8 days. In the second phase, the same piglets were used in resident-intruder tests to verify the potential of the feeding system to interrupt aggressive behaviour. The analysis of all training rounds revealed that piglets learned the commands during 8 days of training and the interest of the piglets increased within training days (P < 0.05). In the resident-intruder test, 79.5% of aggressive interactions were broken by feeder activation. In interactions where either the aggressor or the receiver reacted, a high number of fights were stopped (96.7% versus 93.1%) indicating that it was not relevant if the aggressor or the receiver responded to the feeder activation. We conclude that the electronic feeding system has the potential to be used as cognitive enrichment for piglets, being suitable for reducing aggressive behaviour in resident-intruder situations.