X
XLinkedinWhatsAppTelegramTelegram
0
1
Read this article in:

Using infrared skin temperature to predict stress in piglets

The stress conditions with the highest accuracy in the detection were cold and thirst. Infrared skin temperature is a promising assessment of stress conditions.

2 June 2020
X
XLinkedinWhatsAppTelegramTelegram
0
1

Pork consumption grows about 5% per year in developing countries. Ensuring food safety within ethical standards of meat production is a growing consumer’ demand. The present study aimed to develop a model to predict stress in piglets based on the infrared skin temperature (IST) using machine learning and the paraconsistent logic. A total of 72 piglets (32 males and 40 females) from 1 to 52 days old had the infrared skin temperature recorded during the farrowing and nursery phases under different stress conditions (pain, cold/heat, hunger, and thirst). The assessment of the thermal images was done using an infrared thermography camera. Thermograms were taken at ambient air temperatures ranging from 24 to 30 °C. The minimum infrared skin temperature (IST min) and the maximum infrared skin temperature (ISTmax) and the piglet sex were used as attributes to find the stress conditions (target). The attributes considered in the analysis were classified using the data mining method. The imaging technique is subject to certain contradictions and uncertainties that require mathematical modeling. The paraconsistent logic was applied to extract the contradiction from the data.

The stress condition that had higher accuracy in the detection was that predicted by the cold (100%) using the ISTmin, and ISTmin plus the piglet sex, and thirst (91%) using ISTmax and ISTmax plus the piglet sex. The highest prediction of hunger was found using ISTmin (86%). Although the model was precise in detecting those stresses, the other stressful conditions in piglets such as pain that had an accuracy equal or less than 50%.

Results indicate a promising assessment of stress condition in piglets using infrared skin temperature. We suggest the inclusion of other attributes in the machine learning process to amplify the use of the model.

Felipe Napolitano da Fonseca, Jair Minoro Abe, Irenilza de Alencar Nääs, Alexandra Ferreira da Silva Cordeiro, Fábio Vieira do Amaral, Henry Costa Ungaro, Automatic prediction of stress in piglets (Sus Scrofa) using infrared skin temperature, Computers and Electronics in Agriculture, Volume 168, 2020 https://doi.org/10.1016/j.compag.2019.105148.

Article Comments

This area is not intended to be a place to consult authors about their articles, but rather a place for open discussion among pig333.com users.
Leave a new Comment

Access restricted to 333 users. In order to post a comment you must be logged in.

You are not subscribed to this list Swine News

Swine industry news in your email

Log in and sign up on the list

Related articles

You are not subscribed to this list Swine News

Swine industry news in your email

Log in and sign up on the list