| Title: | Pig weight estimation according to RGB image analysis |
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| Authors: | ID Kárpinszky, Andras (Author)
ID Dobsinszki, Gergely (Author) |
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| Files: |  https://journals.um.si/index.php/agricultura/article/view/2801
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| Language: | English |
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| Work type: | Scientific work |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FKBV - Faculty of Agriculture and Life Sciences
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| Abstract: | In pig farming, knowing the exact weight of each animal is critical for the owner. Such information can help determine the amount and type of feed that needs to be fed to a specific fattening pig. Weighing pigs has always been problematic, because it is highly time consuming, and herding the pigs on the scale is extremely cumbersome. Moreover, it causes stress to the animals. The aim of our study was to build an RGB-based system that could estimate the daily weight of pigs and individual animal weight. The study was set up in a 100-day rotation in a commercial pig farm where we monitored 32 pigs. We developed a system to identify the features of the pigs, more particularly the head, shoulder, belly, and rump part. Three different models
were tested, and their main differences were linked to image processing and training data. Using these models, we received higher than 97% accuracy between the predicted and the manually recorded weight of the animals. This system allows owners to manage and monitor their pigs using our web interface, allowing them to make crucial decisions during the farming process. |
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| Keywords: | image processing, pig size, decision support system, precision livestock farming |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Publication date: | 01.05.2023 |
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| Year of publishing: | 2023 |
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| Number of pages: | str. 51-60 |
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| Numbering: | Vol. 20, no. 1 |
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| PID: | 20.500.12556/DKUM-92625  |
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| UDC: | 636.4:004.9 |
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| ISSN on article: | 2820-610X |
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| COBISS.SI-ID: | 154658307 |
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| DOI: | 10.18690/agricsci.20.1.6 |
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| Publication date in DKUM: | 25.04.2025 |
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| Views: | 167 |
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| Downloads: | 7 |
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| Metadata: |    |
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| Categories: | Misc.
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