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迈向用于监测动物健康的传感器的实际应用:产后健康问题对反刍持续时间、活动和产奶量的影响。

Towards practical application of sensors for monitoring animal health: the effect of post-calving health problems on rumination duration, activity and milk yield.

作者信息

Steensels Machteld, Maltz Ephraim, Bahr Claudia, Berckmans Daniel, Antler Aharon, Halachmi Ilan

机构信息

Institute of Agricultural Engineering,Agricultural Research Organization (ARO) - the Volcani Center,PO Box 6,Bet-Dagan 50250,Israel.

Department of Biosystems (BIOSYST),KU Leuven,Kasteelpark Arenberg 30 - bus 2456,3001 Heverlee,Belgium.

出版信息

J Dairy Res. 2017 May;84(2):132-138. doi: 10.1017/S0022029917000176.

Abstract

Three sources of sensory data: cow's individual rumination duration, activity and milk yield were evaluated as possible indicators for clinical diagnosis, focusing on post-calving health problems such as ketosis and metritis. Data were collected from a computerised dairy-management system on a commercial dairy farm with Israeli Holstein cows. In the analysis, 300 healthy and 403 sick multiparous cows were studied during the first 3 weeks after calving. A mixed model with repeated measurements was used to compare healthy cows with sick cows. In the period from 5 d before diagnosis and treatment to 2 d after it, rumination duration and activity were lower in the sick cows compared to healthy cows. The milk yield of sick cows was lower than that of the healthy cows during a period lasting from 5 d before until 5 d after the day of diagnosis and treatment. Differences in the milk yield of sick cows compared with healthy cows became greater from 5 to 1 d before diagnosis and treatment. The greatest significant differences occurred 3 d before diagnosis for rumination duration and 1 d before diagnosis for activity and milk yield. These results indicate that a model can be developed to automatically detect post-calving health problems including ketosis and metritis, based on rumination duration, activity and milk yield.

摘要

对三种感官数据来源

奶牛个体的反刍时长、活动量和产奶量进行了评估,看其是否有可能作为临床诊断的指标,重点关注产后健康问题,如酮病和子宫炎。数据来自一个商业化奶牛场的计算机化奶牛管理系统,该奶牛场饲养的是以色列荷斯坦奶牛。在分析中,对300头健康经产奶牛和403头患病经产奶牛在产犊后的前三周进行了研究。采用具有重复测量的混合模型来比较健康奶牛和患病奶牛。在从诊断和治疗前5天到诊断和治疗后2天的这段时间里, 患病奶牛的反刍时长和活动量低于健康奶牛。在从诊断和治疗前5天到诊断和治疗后5天的这段时间里,患病奶牛的产奶量低于健康奶牛。与健康奶牛相比,患病奶牛产奶量的差异在诊断和治疗前5天到1天之间变得更大。反刍时长在诊断前3天、活动量和产奶量在诊断前1天出现最大显著差异。这些结果表明,可以开发一个模型,基于反刍时长、活动量和产奶量自动检测包括酮病和子宫炎在内的产后健康问题。

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