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群体饲养火鸡中自动检测到的啄食行为

Automatically Detected Pecking Activity in Group-Housed Turkeys.

作者信息

Gonzalez Jennifer J, Nasirahmadi Abozar, Knierim Ute

机构信息

Farm Animal Behaviour and Husbandry Section, University of Kassel, 37213 Witzenhausen, Germany.

Agricultural and Biosystems Engineering Section, University of Kassel, 37213 Witzenhausen, Germany.

出版信息

Animals (Basel). 2020 Nov 4;10(11):2034. doi: 10.3390/ani10112034.

DOI:10.3390/ani10112034
PMID:33158208
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7694255/
Abstract

In search for an early warning system for cannibalism, in this study a newly developed automatic pecking activity detection system was validated and used to investigate how pecking activity changes over the rearing phase and before cannibalistic outbreaks. Data were recorded on two farms, one with female (intact beaks) and the other with male (trimmed beaks) turkeys. A metallic pecking object that was equipped with a microphone was installed in the barn and video monitored. Pecking activity was continuously recorded and fed into a CNN (Convolutional neural network) model that automatically detected pecks. The CNN was validated on both farms, and very satisfactory detection performances were reached (mean sensitivity/recall, specificity, accuracy, precision, and F1-score around 90% or higher). The extent of pecking at the object differed between farms, but the objects were used during the whole recording time, with highest activities in the morning hours. Daily pecking frequencies showed a low downward trend over the rearing period, although on both farms they increased again in week 5 of life. No clear associations between pecking frequencies and in total three cannibalistic outbreaks on farm 1 in one batch could be found. The detection system is usable for further research, but it should be further automated. It should also be further tested under various farm conditions.

摘要

为了寻找同类相食的早期预警系统,在本研究中,一个新开发的自动啄食活动检测系统得到了验证,并用于研究啄食活动在饲养阶段以及同类相食爆发前是如何变化的。在两个农场记录了数据,一个农场饲养雌性(喙完整)火鸡,另一个农场饲养雄性(喙修剪过)火鸡。在鸡舍中安装了一个配备麦克风的金属啄食物体,并进行视频监控。连续记录啄食活动,并将其输入到一个能自动检测啄食的卷积神经网络(CNN)模型中。该CNN在两个农场都得到了验证,检测性能非常令人满意(平均灵敏度/召回率、特异性、准确率、精确率和F1分数约为90%或更高)。不同农场对物体的啄食程度有所不同,但在整个记录期间都使用了这些物体,上午时段的活动最为频繁。在饲养期间,每日啄食频率呈较低的下降趋势,不过在两个农场,火鸡5周龄时啄食频率又再次上升。在一批饲养的农场1中,未发现啄食频率与总共三次同类相食爆发之间有明显关联。该检测系统可用于进一步研究,但应进一步实现自动化。还应在各种农场条件下进行进一步测试。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3774/7694255/0b500ec069c3/animals-10-02034-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3774/7694255/4af7462019e0/animals-10-02034-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3774/7694255/34d65ff8b573/animals-10-02034-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3774/7694255/94d76609807c/animals-10-02034-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3774/7694255/0b500ec069c3/animals-10-02034-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3774/7694255/4af7462019e0/animals-10-02034-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3774/7694255/34d65ff8b573/animals-10-02034-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3774/7694255/94d76609807c/animals-10-02034-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3774/7694255/0b500ec069c3/animals-10-02034-g004.jpg

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A Sound Source Localisation Analytical Method for Monitoring the Abnormal Night Vocalisations of Poultry.一种用于监测家禽异常夜间发声的声源定位分析方法。
Sensors (Basel). 2018 Sep 1;18(9):2906. doi: 10.3390/s18092906.
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Characteristics of biter and victim piglets apparent before a tail-biting outbreak.
咬尾发生前明显的咬尾癖和受害仔猪特征。
Animal. 2011 Apr;5(5):767-75. doi: 10.1017/S1751731110002326.
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[Examination of the prevalence of skin injuries in debeaked fattened turkeys].[断喙育肥火鸡皮肤损伤患病率的调查]
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Vocalisations and acoustic parameters of flock noise from feather pecking and non-feather pecking laying flocks.啄羽和非啄羽蛋鸡群的群体噪声的发声及声学参数
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Time-budgets, comfort behaviours and injurious pecking of turkeys housed in pairs.成对饲养火鸡的时间分配、舒适行为及有害啄羽行为
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