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使用累积链接混合模型识别与奶牛运动评分相关的奶牛个体水平因素和农场特征。

Identifying cow - level factors and farm characteristics associated with locomotion scores in dairy cows using cumulative link mixed models.

作者信息

Oehm Andreas W, Merle Roswitha, Tautenhahn Annegret, Jensen K Charlotte, Mueller Kerstin-Elisabeth, Feist Melanie, Zablotski Yury

机构信息

Clinic for Ruminants with Ambulatory and Herd Health Services, Ludwig-Maximilians Universität Munich, Oberschleissheim, Germany.

Institute for Veterinary Epidemiology and Biostatistics, Freie Universitaet Berlin, Berlin, Germany.

出版信息

PLoS One. 2022 Jan 28;17(1):e0263294. doi: 10.1371/journal.pone.0263294. eCollection 2022.

DOI:10.1371/journal.pone.0263294
PMID:35089972
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8797239/
Abstract

Lameness is a tremendous problem in intensively managed dairy herds all over the world. It has been associated with considerable adverse effects on animal welfare and economic viability. The majority of studies have evaluated factors associated with gait disturbance by categorising cows into lame and non-lame. This procedure yet entails a loss of information and precision. In the present study, we extend the binomial response to five categories acknowledging the ordered categorical nature of locomotion assessments, which conserves a higher level of information. A cumulative link mixed modelling approach was used to identify factors associated with increasing locomotion scores. The analysis revealed that a low body condition, elevated somatic cell count, more severe hock lesions, increasing parity, absence of pasture access, and poor udder cleanliness were relevant variables associated with higher locomotion scores. Furthermore, distinct differences in the locomotion scores assigned were identified in regard to breed, observer, and season. Using locomotion scores rather than a dichotomised response variable uncovers more refined relationships between gait disturbances and associated factors. This will help to understand the intricate nature of gait disturbances in dairy cows more deeply.

摘要

跛行是全球集约化管理奶牛群中一个严重的问题。它与对动物福利和经济可行性的相当大的不利影响有关。大多数研究通过将奶牛分为跛行和非跛行来评估与步态障碍相关的因素。然而,这个过程会导致信息和精度的损失。在本研究中,我们将二项式反应扩展为五类,承认运动评估的有序分类性质,从而保留了更高水平的信息。使用累积链接混合建模方法来识别与运动评分增加相关的因素。分析表明,体况差、体细胞计数升高、跗关节病变更严重、胎次增加、无法进入牧场以及乳房清洁度差是与较高运动评分相关的相关变量。此外,在品种、观察者和季节方面,所分配的运动评分存在明显差异。使用运动评分而不是二分反应变量可以揭示步态障碍与相关因素之间更精细的关系。这将有助于更深入地理解奶牛步态障碍的复杂性质。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d591/8797239/f8168abb58d7/pone.0263294.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d591/8797239/f8168abb58d7/pone.0263294.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d591/8797239/f8168abb58d7/pone.0263294.g001.jpg

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