| Issue |
E3S Web Conf.
Volume 328, 2021
International Conference on Science and Technology (ICST 2021)
|
|
|---|---|---|
| Article Number | 04021 | |
| Number of page(s) | 4 | |
| Section | Information System, Big Data, Design Application, IOT | |
| DOI | https://doi.org/10.1051/e3sconf/202132804021 | |
| Published online | 06 December 2021 | |
Reproductive Behavior’s: Audiovisual detection of oestrus after synchronization using Prostaglandin F2 Alpha (PGF2α)
1 Departmen of Animal Husbandry, University Musamus, 99611 Merauke, Indonesia
2 Departmen of Informatic, University Musamus, 99611 Merauke, Indonesia
* Corresponding author : nurcholis@unmus.ac.id
Artificial insemination program to increase production is affected by oestrus. Breeders generally identify cows in oestrus based on their behavior. Currently, oestrus can be predicted and scheduled due to PGF2α synchronization. This study aims to determine the detection of oestrus after PGF2α synchronization, and more specifically to distinguish audio-visual behavior. The six cows used were synchronized using PGF2α. Descriptive methods include (mean, standard deviation). Test. Chi-square was used for qualitative data comparison. The observed variables were the onset of oestrus and lust behavior (looking at the audiovisual characteristics, using video and the Audio Spectrum Monitor (ASM) application. The results showed that the response to oestrus appeared 30 hours after synchronization in 5 cows. The visual behavior that appears a lot is Mounting activity, Mucus Exit, Vulva Swelling, Restlessness and Vocalization duration. ASM recordings show the frequency in cows that are in oestrus between 405 Hz -485 Hz after PGF2α injection. In conclusion, the audiovisual behavior of cows after synchronization shows that the cows are in a state of oestrus, and are ready for artificial insemination.
Key words: Audiovisual Behavior / PGF2α / Oestrus Detection
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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