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基于反刍、活动和产奶量警报的自动健康监测与目视观察对牛群健康监测和生产性能结果的影响。

Effect of automated health monitoring based on rumination, activity, and milk yield alerts versus visual observation on herd health monitoring and performance outcomes.

作者信息

Rial C, Stangaferro M L, Thomas M J, Giordano J O

机构信息

Department of Animal Science, Cornell University, Ithaca, NY 14853.

Dairy Health and Management Services, Lowville, NY 13367.

出版信息

J Dairy Sci. 2024 Dec;107(12):11576-11596. doi: 10.3168/jds.2024-25256. Epub 2024 Sep 27.

DOI:10.3168/jds.2024-25256
PMID:39343202
Abstract

A primary objective of this randomized trial was to compare the percentage of cows that underwent clinical examination and were diagnosed with clinical health disorders (CHD) using a health monitoring program that relied only on automated monitoring system alerts versus a program that relied only on visual observation of clinical signs of disease to select cows for clinical examination. Another objective was to compare the effects of these health monitoring programs on milk yield, the herd exit dynamics (i.e., cows sold and dead), and first service reproductive outcomes. Lactating Holstein cows (n = 1,204) enrolled in the experiment were fitted with a neck-attached sensor of an automated monitoring system (HR Tags; Merck & Co. Inc.) that generated health alerts based on rumination time and activity. Milk yield was monitored 3 times per day by automated milk meters (MM27BC, DeLaval). Cows were blocked by parity, close-up period diet, and stratified by previous lactation milk yield, and then were randomly assigned within block to different programs for monitoring health from 3 to 21 DIM. Cows in the visual observation group (VO; n = 597) were selected for clinical examination exclusively based on visual observation of clinical signs of disease, whereas cows in the automated health monitoring group (AHM; n = 607) were selected for clinical examination based on health alerts consisting of the following: a health index score <86 arbitrary units, daily rumination <250 min, or a reduction of >20% in daily milk yield. Once selected for examination, the clinical exam was the same for both treatment groups. Binary data such as the occurrence of CHD, herd exit, and pregnancies per AI were analyzed with logistic regression. Daily and weekly milk yield were analyzed using ANOVA with repeated measurements. More cows underwent a clinical examination, more cows were diagnosed with at least one CHD, and more cows received treatment in the AHM group than the VO treatment group. Cows in the AHM treatment had more accumulated milk than cows in the VO treatment from 2 to 21 DIM. Cows in the AHM treatment diagnosed with at least 1 CHD produced more milk from 3 to 18 and 20 to 21 DIM than cows diagnosed with a CHD in the VO treatment. Fewer cows left the herd up to 21 DIM for the AHM than the VO treatment. Pregnancies per AI at first service were greater for the VO than the AHM treatment at 30 d but not at 50 d after AI, and no difference in pregnancy loss was detected. Overall, a health monitoring strategy that used automated health alerts increased the risk of undergoing clinical examination and having CHD diagnosed compared with a program that selected cows for clinical examination based exclusively on VO. Cows monitored with the program that relied on automated alerts also had greater milk yield in the first 21 DIM. Thus, monitoring cow health based on automated behavior and milk yield alerts might be a more effective alternative for health monitoring than exclusive use of visual observation of clinical signs of disease.

摘要

这项随机试验的主要目的是比较使用仅依赖自动监测系统警报的健康监测程序与仅依靠目视观察疾病临床症状来选择奶牛进行临床检查的程序,接受临床检查并被诊断患有临床健康障碍(CHD)的奶牛百分比。另一个目的是比较这些健康监测程序对产奶量、牛群出栏动态(即售出和死亡的奶牛)以及首次输精繁殖结果的影响。参与实验的1204头泌乳荷斯坦奶牛佩戴了自动监测系统(HR Tags;默克公司)的颈部传感器,该系统根据反刍时间和活动生成健康警报。每天通过自动挤奶器(MM27BC,利拉伐)监测3次产奶量。奶牛按胎次、围产期日粮进行分组,并按上一胎次产奶量分层,然后在组内随机分配到不同的程序,在产犊后3至21天监测健康状况。目视观察组(VO;n = 597)的奶牛仅根据疾病临床症状的目视观察来选择进行临床检查,而自动健康监测组(AHM;n = 607)的奶牛则根据以下健康警报来选择进行临床检查:健康指数得分<86任意单位、每日反刍时间<250分钟或日产奶量减少>20%。一旦被选中进行检查,两个治疗组的临床检查相同。使用逻辑回归分析CHD的发生、牛群出栏和每次人工授精的妊娠等二元数据。使用重复测量的方差分析来分析每日和每周的产奶量。与VO治疗组相比,AHM组接受临床检查的奶牛更多,被诊断患有至少一种CHD的奶牛更多,接受治疗的奶牛也更多。在产犊后2至21天,AHM治疗组的奶牛比VO治疗组的奶牛积累的牛奶更多。在产犊后3至18天以及20至21天,AHM治疗组中被诊断患有至少1种CHD的奶牛比VO治疗组中被诊断患有CHD的奶牛产奶更多。在产犊后21天内,AHM组离开牛群的奶牛比VO治疗组少。首次输精后30天,VO组的每次人工授精妊娠率高于AHM组,但在人工授精后50天没有差异,且未检测到妊娠损失的差异。总体而言,与仅基于目视观察选择奶牛进行临床检查的程序相比,使用自动健康警报的健康监测策略增加了接受临床检查和被诊断患有CHD的风险。使用依赖自动警报的程序监测的奶牛在最初21天内产奶量也更高。因此,基于自动行为和产奶量警报监测奶牛健康可能是一种比仅目视观察疾病临床症状更有效的健康监测替代方法。

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