Determining the growth of pigs in commercial facilities using machine vision: on-farm and offline results
Article
Article Title | Determining the growth of pigs in commercial facilities using machine vision: on-farm and offline results |
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ERA Journal ID | 3449 |
Article Category | Article |
Authors | Tscharke, M. (Author) and Banhazi, T. M. (Author) |
Journal Title | Australian Journal of Multi-Disciplinary Engineering |
Journal Citation | 10 (1), pp. 26-40 |
Number of Pages | 15 |
Year | 2013 |
Publisher | Taylor & Francis |
Place of Publication | Australia |
ISSN | 0812-3314 |
1441-6611 | |
1448-8388 | |
Digital Object Identifier (DOI) | https://doi.org/10.7158/14488388.2013.11464862 |
Abstract | A vision system was developed to determine the live weight of pigs from their body measurements non-invasively. This article presents on-farm and offline results obtained from the piGUI system while estimating the weight of grower pigs. During the on-farm trial the system recorded the growth of four successive batches of grower pigs at a commercial piggery. The growth output from the system was used to demonstrate the system’s potential in detecting the effect of undesirable conditions in practice. As according to the system, extreme summer temperatures may |
Keywords | machine vision, precision livestock farming, pigs; weight estimation, smart farming, temperature, activity |
ANZSRC Field of Research 2020 | 300302. Animal management |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | National Centre for Engineering in Agriculture |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q5533/determining-the-growth-of-pigs-in-commercial-facilities-using-machine-vision-on-farm-and-offline-results
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