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H2020Individual fellowship2020–2021

AutoPlayPig · Automatic detection of play behaviour in young pigs as a measure of positive affective states.

Horizon 2020 — Marie Skłodowska-Curie Actions

Duration
2020-01-01 → 2021-12-31
EU contribution
€178,320
Participants
1
Scheme
MSCA-IF-EF-ST

Lines connect the coordinator with its partners.

Results in brief

Automatic detection of play behaviour in young pigs as a measure of positive affective states.

The welfare of livestock animals is of high concern, not only to the farmer but also to the consumer and general public. It has in recent years become clear that optimal animal well-being is not merely the removal of negative experiences, but also the presence of positive experiences, meaning that even production animals should have a live worth living. Play behaviour in pigs could be an indicator of both the lack of negative and the presence of positive experiences. However, it is not possible for farmers, consultants or inspectors to observe play behaviour in young pigs as it occurs spontaneous and is very short lasting when it occurs. Thus, to use play behaviour for welfare assessment in pigs, the observations need to be performed automatically. One objective of project AutoPlayPig is to take the first steps in developing an algorithm for automatic detection of play behaviour in young pigs. More research is also needed to elucidate whether play behaviour in young pigs can be considered a measure of animal well-being. Thus, a second objective of project AutoPlayPig is to further validate play behaviour as a welfare indicator in young pigs by investigating the level of play behaviour of the individual pig, how it relates to the presence and absence of welfare threats such as weaning, ear damage and diarrhoea and how it is related to factors indicating a better thrive such as higher growth. The project was successful in providing a proof of concept that locomotor play can be observed automatically from video, while also achieving its aim of further validating play behaviour as a welfare indicator in pigs, by providing evidence that play behaviour in young pigs is performed less in the presence of the investigated welfare threats, while being performed more in pigs that show indicators of better well-being.

Data: CORDIS, © European Union

Project objective

The welfare of animals kept for human consumption is of high concern globally, also within the European Commission including the welfare of the domesticated pig . As animal well-being is not just the absence of negative affective states, but also, and probably predominantly, the presence of positive affective states, identifying indicators of positive affective states in farmed animals can increase our capacity to improve their health and welfare. One such indicator is play behaviour. Play in pigs is an event occurring sporadically. Thus, using play behaviour for welfare assessment will not be possible through direct observations. Instead, it demands automation and continuous monitoring, two key elements of Precision Livestock Farming (PLF). The current project aims to investigate the relation between play behaviour in pigs and sensor data from image and sound analysis combining ethology and computer science into one field of Computational Ethology (CE). The project will focus on the CE part of the research, but the knowledge obtained could be used to develop real-time PLF algorithms for use in pig herds to observe the frequency and duration of play behaviour at pen level, beneficial to both the farmer, consultants, inspectors and future research projects within play behaviour in pigs. Training of the reseacher will include a thorough introduction to the field of CE and PLF, to the decoding and labeling of feature variables and to the use of machine learning algorithms on sensor data; all expertise fields of the hosting research group. All in all, the current project will take the first steps in developing a method for automatic recognition of play behaviour and positive affective states in pigs, as well as training the researcher for a future career within Computational Ethology and Precision Livestock Farming.

Original text from CORDIS.

Participants

  • KATHOLIEKE UNIVERSITEIT LEUVEN · LeuvenCoordinatorBelgium

Links

Data: CORDIS, © European Union