van Erp-van der Kooij Elaine, de Graaf Lois F, de Kruijff Dennis A, Pellegrom Daphne, de Rooij Renilda, Welters Nian I T, van Poppel Jeroen
Department of Animal Husbandry, HAS Green Academy, University of Applied Sciences, P.O. Box 90108, 5200 MA 's-Hertogenbosch, The Netherlands.
Department of Applied Biology, HAS Green Academy, University of Applied Sciences, P.O. Box 90108, 5200 MA 's-Hertogenbosch, The Netherlands.
Animals (Basel). 2023 Nov 16;13(22):3538. doi: 10.3390/ani13223538.
Precision Livestock Farming systems can help pig farmers prevent health and welfare issues around farrowing. Five sows were monitored in two field studies. A Sorama L642V sound camera, visualising sound sources as coloured spots using a 64-microphone array, and a Bascom XD10-4 security camera with a built-in microphone were used in a farrowing unit. Firstly, sound spots were compared with audible sounds, using the Observer XT (Noldus Information Technology), analysing video data at normal speed. This gave many false positives, including visible sound spots without audible sounds. In total, 23 of 50 piglet births were visible, but none were audible. The sow's behaviour changed when farrowing started. One piglet was silently crushed. Secondly, data were analysed at a 10-fold slower speed when comparing sound spots with audible sounds and sow behaviour. This improved results, but accuracy and specificity were still low. When combining audible sound with visible sow behaviour and comparing sound spots with combined sound and behaviour, the accuracy was 91.2%, the error was 8.8%, the sensitivity was 99.6%, and the specificity was 69.7%. We conclude that sound cameras are promising tools, detecting sound more accurately than the human ear. There is potential to use sound cameras to detect the onset of farrowing, but more research is needed to detect piglet births or crushing.
精准畜牧养殖系统可以帮助养猪户预防分娩前后的健康和福利问题。在两项实地研究中对五头母猪进行了监测。在一个分娩单元中使用了一台索拉玛L642V声音摄像机，它使用64个麦克风阵列将声源可视化为彩色斑点，以及一台内置麦克风的巴斯科姆XD10 - 4安全摄像机。首先，使用Observer XT（诺德斯信息技术公司）以正常速度分析视频数据，将声音斑点与可听声音进行比较。这产生了许多误报，包括没有可听声音的可见声音斑点。在总共50次仔猪出生中，有23次可见，但无一可听。分娩开始时母猪的行为发生了变化。有一头仔猪被悄悄压死。其次，在将声音斑点与可听声音及母猪行为进行比较时，以慢10倍的速度分析数据。这改善了结果，但准确性和特异性仍然较低。当将可听声音与可见的母猪行为相结合，并将声音斑点与声音和行为的组合进行比较时，准确率为91.2%，误差为8.8%，灵敏度为99.6%，特异性为69.7%。我们得出结论，声音摄像机是很有前景的工具，比人耳更准确地检测声音。有潜力使用声音摄像机来检测分娩的开始，但需要更多研究来检测仔猪出生或挤压情况。
