Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6540101 | Computers and Electronics in Agriculture | 2016 | 7 Pages |
Abstract
The model detected a rise in activity on average 13 ± 4.8 h (mean ± standard deviation) before farrowing in sows housed in crates and pens with sensitivity of 96.7% and specificity of 100%. The fact that we were able to use a single model with a constant set of parameters gives indication that the method has potential to become a robust indicator of farrowing in different housing systems, even though pre-farrowing activity was higher in sows housed in pens than in crates.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Matti Pastell, Juha Hietaoja, Jinhyeon Yun, Johannes Tiusanen, Anna Valros,