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从奶牛乳腺炎指标面板中的常见趋势量化乳腺炎的严重程度。

Quantifying degree of mastitis from common trends in a panel of indicators for mastitis in dairy cows.

机构信息

Faculty of Agricultural Sciences, Aarhus University, Tjele, DK-8830, Denmark.

出版信息

J Dairy Sci. 2010 Feb;93(2):582-92. doi: 10.3168/jds.2009-2445.

Abstract

This paper has 2 objectives. First, it argues that it is beneficial to regard degree of infection with respect to mastitis as a latent quantity varying continuously from 0 (truly healthy) to 1 (full-blown clinical mastitis). This quantity is denoted as degree of infection (DOI). The DOI is based on extracting common characteristics from a panel of indicators measured repeatedly over time. The indicators used in this paper are electrical conductivity (EC), somatic cell count (SCC), and the immune response related enzyme lactate dehydrogenase (LDH). Second, this paper presents a statistical model for such data and a corresponding method for estimating the DOI from a panel of indicators. An empirical proof of concept is provided. Using DOI, there was a significant difference between the DOI of mastitic and healthy control cows beginning 5 d before the mastitic cows were treated for mastitis.

摘要

本文有 2 个目标。首先,它认为将乳腺炎的感染程度视为一个连续变化的潜在变量,从 0(真正健康)到 1(完全临床乳腺炎)是有益的。这个数量被表示为感染程度(DOI)。DOI 是基于从随时间重复测量的一组指标中提取共同特征而得出的。本文使用的指标是电导率(EC)、体细胞计数(SCC)和与免疫反应相关的酶乳酸脱氢酶(LDH)。其次,本文提出了一种用于此类数据的统计模型,以及一种从一组指标中估计 DOI 的相应方法。提供了一个经验概念验证。使用 DOI,在乳腺炎奶牛接受乳腺炎治疗前 5 天,乳腺炎奶牛和健康对照组奶牛的 DOI 之间存在显著差异。

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