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使用多种商业化精准奶牛监测技术对同步发情奶牛进行自动发情检测。

Automated estrous detection using multiple commercial precision dairy monitoring technologies in synchronized dairy cows.

机构信息

Department of Animal and Food Sciences, University of Kentucky, Lexington 40546.

Department of Animal and Dairy Sciences, Mississippi State University, Starkville 39762.

出版信息

J Dairy Sci. 2019 Mar;102(3):2645-2656. doi: 10.3168/jds.2018-14738. Epub 2019 Jan 26.

Abstract

Estrus in dairy cattle varies in duration and intensity, highlighting the need for accurate and continuous monitoring to determine optimal breeding time. The objective of this study was to evaluate precision dairy monitoring technologies (PDMT) for detecting estrus. Estrus was synchronized in lactating Holstein cows (n = 109) using a modified G7G-Ovsynch protocol (last GnRH injection withheld to permit expression of estrus) beginning at 45 to 85 d in milk. Resumption of ovarian cyclicity at enrollment was verified by transrectal ultrasonography for presence of a corpus luteum. Cows were observed visually during 30 min (4 times per day) for behavioral estrus on d -1 to 2 (d 0 = day of estrus). Periods peri-estrus were defined by the temporal blood plasma progesterone patterns on d -5, -4, -3, -2, -1, 0, 2, 4, 6, and 8. Estrous detection by PDMT, an estrous behavior scoring system, and by visual observation of standing estrus were compared with the reference (gold) standard. Only 56% of cows that ovulated were observed standing by visual observation. Sensitivity and specificity for estrous detection were not different among all PDMT. Devices in this study measuring activity in steps, neck movement, high activity of head movement, or a proprietary motion index increased on the day of estrus 69 to 170% from the baseline before estrus. The change in rumination time on the day of estrus decreased for both neck and ear-based technologies (-2 to -16%). Temperature of the reticulorumen, vagina, and ear skin were not different on the day of estrus than day peri-estrus. Daily lying times decreased on average to 24.6% on the day of estrus for IceQube (IceRobotics Ltd., Edinburgh, Scotland). In contrast, lying time increased 15.5 and 33.1% for AfiAct Pedometer Plus (Afimilk, Kibbutz Afikim, Israel) and Track a Cow (ENGS Systems Innovative Dairy Solutions, Rosh Pina, Israel), respectively. All PDMT tested were capable of detecting estrus at least as effectively as visual observation. Four of the 6 PDMT that reported estrous alerts correctly detected 15 to 35% more cows than visual observation 4 times per day. Use of temporal progesterone patterns correctly identified more cows than visual observation alone. Dairy producers considering PDMT should focus on (1) the reference (gold) standard used to test efficacy of a device's alerts and (2) the device that will have the fewest false readings in their operations.

摘要

奶牛的发情持续时间和强度各不相同,这突出表明需要进行准确和连续的监测,以确定最佳配种时间。本研究的目的是评估精确奶牛监测技术(PDMT)在检测发情方面的效果。使用改良的 G7G-Ovsynch 方案(最后一次 GnRH 注射被保留,以允许发情表达),对泌乳荷斯坦奶牛(n = 109)进行发情同步,发情同步开始于产奶后 45 至 85 天。通过直肠超声检查确认发情恢复,以检测黄体的存在。在 d-1 至 2 天(d0 = 发情日)期间,奶牛通过视觉观察(每天 4 次,每次 30 分钟)进行行为发情观察。发情期的界定是基于 d-5、-4、-3、-2、-1、0、2、4、6 和 8 天的血浆孕酮模式。通过 PDMT、发情行为评分系统和站立发情的视觉观察来检测发情,并与参考(金)标准进行比较。只有 56%的排卵奶牛被视觉观察到站立发情。所有 PDMT 的发情检测敏感性和特异性没有差异。本研究中,测量步数、颈部运动、头部运动高活跃度或专有运动指数的设备在发情日从发情前的基线增加了 69%至 170%。发情日反刍时间的变化在颈部和耳部技术中减少了 2 至 16%(-2 至-16%)。发情日的网胃温度、阴道温度和耳部皮肤温度与发情期前没有差异。与发情日相比,IceQube(IceRobotics Ltd.,爱丁堡,苏格兰)的平均躺卧时间减少了 24.6%。相比之下,AfiAct Pedometer Plus(Afimilk,以色列基布兹阿菲克姆)和 Track a Cow(ENGS Systems innovative Dairy Solutions,以色列罗什皮纳)的躺卧时间分别增加了 15.5%和 33.1%。本研究中测试的所有 PDMT 至少与视觉观察一样有效地检测发情。在 6 种 PDMT 中,有 4 种报告发情警报的设备比视觉观察(每天 4 次)检测到的奶牛多 15%至 35%。使用时间孕酮模式可以比单独使用视觉观察更准确地识别出更多的奶牛。考虑使用 PDMT 的奶农应关注(1)用于测试设备警报效果的参考(金)标准,以及(2)在其运营中误报最少的设备。

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