Scientists at Scotland’s Rural College (SRUC) Pig Research Centre in Penicuik, Midlothian are using a new pig facial recognition tool to help assess the emotional wellbeing of the animals.
The tool works by scanning the pig’s face to determine if its facial expression is content or distressed. Highly expressive and intelligent animals, previous SRUC studies have successfully demonstrated that pigs are able to communicate their mood and intentions to each other using different facial expressions.
To develop this technology, researchers on the project have been capturing 3D and 2D facial images of the breeding sow population. The images are then sent to the University of West of England (UWE) for processing, where methods are being developed to automatically identify the pig’s different emotions.
Researchers say that the tool could be developed to monitor individual faces and alert farmers to health and welfare problems as it will be able to tell if they are happy, sad, in pain or content.
The tool has great potential to help manage pain for the livestock. For example, sows experiencing lameness could benefit if the tool is able to distinguish and identify facial expressions to show pain before and after receiving medication.
Prof Melvyn Smith, from UWE Bristol’s Centre for Machine Vision, said: “Machine vision technology offers the potential to realise a low-cost, non-intrusive and practical means to biometrically identify individual animals on the farm.
“Our work has already demonstrated a 97% accuracy at facial recognition in pigs. Our next step will be, for the first time, to explore the potential for using machine vision to automatically recognise facial expressions that are linked with core emotion states, such as happiness or distress, in the identified pigs.”
Dr Emma Baxter, from SRUC, believes that the research could result in savings for farmers: “Early identification of pig health issues gives farmers the potential to improve animal wellbeing by tackling any problems quickly and implementing tailored treatment for individuals.
“This will reduce production costs by preventing the impact of health issues on performance.”