Researchers decode pigs' well-being through oinks and grunts

European researchers have developed a way of decoding the feelings of pigs through their grunts, oinks and squeals.

Biologists studied over 7,000 recordings from 411 pigs, from the brief squeaks of satisfaction at feeding time to the desperate cries at slaughter, and then categorized them into 19 different categories.

The leader of the project said it was possible to figure out the emotions of the pigs by their vocalizations.

According to the researcher, the project offers a new way of improving animal welfare by laying the groundwork for a tool that can categorize an emotion based on the noise produced.

We run a machine learning program that learns to recognize negative and positive contexts.

Farmers would be able to monitor their mental health once the new tool is developed.

The researcher said that if the negative squeals increased, the farmer could check to see if something was wrong.

The results of the study are promising, as the country with the most pigs in Europe has over two per capita.

Trine Vig, a spokeswoman for the council, said that the concept could be used to monitor the health and well-being of pigs.

They are very vocal.

According to Briefer, they reached 92 percent accuracy of classifying the sound as positive or negative.

Positive feelings are most often expressed with short grunts, while negative feelings are most often expressed with longer sounds.

Why not focus on the pig instead of the other animals?

The pig, known for its wide range of noises, was the perfect match for the study.

The researcher said that they are very vocal, which makes them easier to study.

Even in a low intensity situation, they would still vocalize.

More information: Elodie F. Briefer et al, Classification of pig calls produced from birth to slaughter according to their emotional valence and context of production, Scientific Reports (2022). DOI: 10.1038/s41598-022-07174-8 Journal information: Scientific Reports

There will be a new year in 2022.

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