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利用摄像机图像分析预测日本黑牛的产犊时间。

Predicting the start of calving in Japanese Black cattle using camera image analysis.

机构信息

Laboratory of Animal Feeding and Management, Department of Animal Science, School of Veterinary Medicine, Kitasato University, Aomori 034-8628, Japan.

出版信息

J Reprod Dev. 2021 Feb 15;67(1):53-58. doi: 10.1262/jrd.2020-087. Epub 2020 Dec 8.

DOI:10.1262/jrd.2020-087
PMID:33298634
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7902219/
Abstract

This study assessed the feasibility of using camera image analysis to detect behavioral changes as an indicator of the onset of calving in Japanese Black cattle. Thirty-five pregnant cattle individually housed in pens were used and were continuously monitored using a digital camera system. For the automatic determination of the x and y coordinates of a cow, trajectory analysis was conducted using thermal image and analysis software, and the distances moved were calculated using coordinate data. Further, the frequency of postural changes and the time spent tail raising per hour were measured for 14 cows using visible images. The measurement data were used to calculate hourly data for 12 h prior to amniorrhexis (first rupture of the allantoic sac). The hourly distances moved tended to increase at the time of amniorrhexis, with significantly longer distances measured 3-0 h before amniorrhexis than those at 12-8 h before amniorrhexis (P < 0.05). In all cows, amniorrhexis occurred within 11 h of hourly distances moved by more than 50% compared with distance moved the previous hour. The overall average elapsed time before amniorrhexis was 9 h 30 min (range: 5-11 h). Tail raising time and the frequency of postural changes significantly increased at 1-0 h and 2-0 h before amniorrhexis, respectively. This suggests that predicting the time of calving is possible by measuring the activity of Japanese Black cows during late pregnancy using camera image analysis as a non-invasive technique.

摘要

本研究评估了使用相机图像分析检测行为变化作为日本黑牛分娩开始的指标的可行性。35 头单独圈养在畜栏中的怀孕牛使用数字相机系统进行连续监测。为了自动确定牛的 x 和 y 坐标,使用热图像和分析软件进行轨迹分析,并使用坐标数据计算移动的距离。此外,使用可见图像测量了 14 头奶牛的姿势变化频率和每小时尾巴抬起的时间。将测量数据用于计算羊膜破裂前 12 小时(羊膜囊第一次破裂)的每小时数据。在羊膜破裂时,每小时移动的距离趋于增加,与羊膜破裂前 12-8 小时相比,羊膜破裂前 3-0 小时测量的距离明显更长(P <0.05)。在所有奶牛中,与前一小时相比,每小时移动距离超过 50%时,羊膜破裂发生在 11 小时内。羊膜破裂前的总平均时间为 9 小时 30 分钟(范围:5-11 小时)。在羊膜破裂前 1-0 小时和 2-0 小时,尾巴抬起时间和姿势变化频率分别显著增加。这表明,通过使用相机图像分析作为一种非侵入性技术测量日本黑牛妊娠后期的活动,可以预测分娩时间。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c487/7902219/3b7028e85b4f/jrd-67-053-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c487/7902219/1a6467ec1d8b/jrd-67-053-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c487/7902219/bd87ce363cdd/jrd-67-053-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c487/7902219/3481bdb0d593/jrd-67-053-g003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c487/7902219/3b7028e85b4f/jrd-67-053-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c487/7902219/1a6467ec1d8b/jrd-67-053-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c487/7902219/bd87ce363cdd/jrd-67-053-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c487/7902219/3481bdb0d593/jrd-67-053-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c487/7902219/0d28ad69fefc/jrd-67-053-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c487/7902219/098a467b6443/jrd-67-053-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c487/7902219/3b7028e85b4f/jrd-67-053-g006.jpg

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本文引用的文献

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Prevalence, causes, resolution and consequences of bovine dystocia in Italy.意大利牛难产的发生率、病因、解决方法及后果
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