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了解乳腺炎对产奶量的影响动态:解读乳腺炎发生时的发病及恢复模式。

Understanding the dynamics of mastitis in milk yield: Decoding onset and recovery patterns in response to mastitis occurrence.

作者信息

Sguizzato A L L, da Silva T E, Chagas J C C, Argüelo A M, Gonçalves N M, Marcondes M I

机构信息

Department of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, 36570-900, Brazil.

Department of Animal and Veterinary Sciences, University of Vermont, Burlington, VT 05405.

出版信息

JDS Commun. 2024 Jul 14;5(6):669-673. doi: 10.3168/jdsc.2024-0579. eCollection 2024 Nov.

Abstract

No recent study has attempted to model daily milk losses before and after mastitis onset and the moment when it begins. Thus, we aimed to describe the impact of mastitis on milk production based on mastitis level and moment of occurrence. We used data from 11 dairy farms, and the dataset consisted of 885,759 daily individual milk test records from 3,508 cows in different lactations, with an average milk yield (MY) from January 2017 to December 2022. We modeled the impact of mastitis severity (i.e., 1 [mild] and 2 [severe]) based on the drop and recovery of MY following 3 steps. First, we removed milk recorded on the day of diagnosis of mastitis from the dataset and fitted a Wood's curve for each cow and parity. Second, we returned the mastitis data to the dataset and estimated the residual milk loss due to mastitis from 15 d before to 30 d after the mastitis event. Third, we used generalized additive mixed effect models to estimate the residual milk loss, including farm as a random effect. In addition to the random effect of the farm, we also included the predicted milk yield (by Wood's curve) over the influence of mastitis, the day effect before and after mastitis incidence, and the interaction between the predicted value of mastitis and days. On average, mastitis level 2 resulted in a more severe MY drop in all represented stages of lactation (80, 170, and 260 DIM), suggesting a higher loss close to the lactation peak, approximately 130 kg more than mastitis level 1. Moreover, the occurrence of mastitis case level 1 during the early phase of lactation (DIM 80) can cause an average milk loss of 158 L and mastitis level 2, an average loss of 288 L. The estimations suggest that milk drop occurs 14 to 4 d before mastitis onset and can last until 15 to 25 d from the diagnosis, which would be the necessary time for a cow to re-establish their predicted MY. Therefore, our study brings new perspectives to investigate MY drop and recovery due to mastitis infections and how much mastitis can deplete and impair milk production.

摘要

最近没有研究试图对乳腺炎发作前后以及开始时刻的每日产奶量损失进行建模。因此,我们旨在根据乳腺炎的程度和发生时刻来描述乳腺炎对产奶量的影响。我们使用了11个奶牛场的数据,数据集包括来自3508头处于不同泌乳期奶牛的885759条每日个体产奶量测试记录,涵盖了2017年1月至2022年12月的平均产奶量(MY)。我们按照以下3个步骤,根据产奶量的下降和恢复情况,对乳腺炎严重程度(即1级[轻度]和2级[重度])的影响进行建模。首先,我们从数据集中剔除乳腺炎诊断当天记录的产奶量,并为每头奶牛和胎次拟合一条伍德曲线。其次,我们将乳腺炎数据放回数据集中,并估计从乳腺炎事件发生前15天到发生后30天因乳腺炎导致的剩余产奶量损失。第三,我们使用广义相加混合效应模型来估计剩余产奶量损失,将农场作为随机效应纳入其中。除了农场的随机效应外,我们还纳入了受乳腺炎影响的预测产奶量(通过伍德曲线)、乳腺炎发病前后的日效应,以及乳腺炎预测值与天数之间的相互作用。平均而言,在泌乳的所有代表阶段(80天、170天和260天泌乳天数),2级乳腺炎导致的产奶量下降更为严重,这表明在泌乳高峰期附近损失更大,比1级乳腺炎大约多130千克。此外,在泌乳早期(80天泌乳天数)发生1级乳腺炎病例可导致平均产奶量损失158升,而2级乳腺炎平均损失288升。估计结果表明,产奶量下降发生在乳腺炎发作前14至4天,并且可持续到诊断后15至25天,这是奶牛重新建立其预测产奶量所需的时间。因此,我们的研究为调查乳腺炎感染导致的产奶量下降和恢复情况以及乳腺炎会消耗和损害多少产奶量带来了新的视角。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3184/11624389/04e4f4c6ab3e/fx1.jpg

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