利用常规收集的牛群数据评估模型的准确性,以预测农场跛足的流行程度。

IF 3.7 1区 农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE
Conor Barry , Esben Østergaard Eriksen , Kristian Ellingsen-Dalskau , Christoph Winckler , Nicholas J. Bell , Camilla Kielland
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引用次数: 0

摘要

跛足是全球乳制品行业的主要福利和生产问题。量化跛行挑战对畜群健康管理至关重要。由挪威乳品公司开发的“羊爪健康指标”(CHI)是根据挪威奶牛群记录系统中常规收集的数据按月计算的。假设CHI反映了农场的跛行患病率。我们的横断面研究评估了CHI对农场跛足患病率预测的准确性。我们还开发了一种替代模型,利用常规收集的牧群数据(RHD)的附加变量来预测跛行患病率,并评估了其准确性。我们使用了来自149个挪威散养奶牛群的数据。以跛牛和重度跛牛总比例为因变量,每群CHI评分为自变量,建立单变量β回归模型。选取RHD变量,建立具有相同因变量的多变量β回归模型。两种模型的准确性根据其一致性和预测误差进行评估。正如假设的那样,较高的CHI分数表明跛行患病率较低,反之亦然。在我们的样本中,从最低的CHI得分到最高的CHI得分相当于跛行患病率降低了6%。然而,在相同CHI评分的牛群中,跛牛的总比例有很大的差异。CHI模型在预测农场跛足患病率时高度不准确,一致性r为0.05。包含6个RHD自变量的替代RHD模型比CHI模型更准确,但仍不准确,一致性相关系数为0.31。CHI和替代RHD模型都不适合准确预测农场跛足的患病率。虽然它们的组成部分反映了群体水平上的爪健康状况,但它们未能反映奶牛群体跛足的复杂、多因素性质。CHI可能仍然对爪健康管理有用,作为识别农场潜在问题的工具,并激励生产者参与,但需要进一步调查。替代模型中的RHD变量比CHI更简单,更广泛,便于在挪威以外的其他国家或奶牛群中复制和进一步发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating the accuracy of models using routinely collected herd data for prediction of on-farm lameness prevalence
Lameness is a major welfare and production concern for the dairy sector worldwide. Quantifying the lameness challenge is essential for herd health management. The Claw Health Indicator (CHI), developed by a Norwegian dairy company, is calculated on a monthly basis using data routinely collected in the Norwegian Dairy Herd Recording System. The CHI was hypothesized to reflect the lameness prevalence on farm. Our cross-sectional study evaluated the accuracy of predictions made about the lameness prevalence on farm by the CHI. We also developed an alternative model for predicting the lameness prevalence using additional variables of routinely collected herd data (RHD) and evaluated its accuracy. We used data from 149 Norwegian freestall dairy herds. A univariable β regression model was built with the total proportion of lame and severely lame cows as the dependent variable and the CHI score for each herd as the independent variable. A second model, a multivariable β regression model with the same dependent variable, was built using selected variables of RHD. The accuracy of both models was assessed in terms of their concordance r and prediction errors. A higher CHI score was indicative, as hypothesized, of a lower lameness prevalence and vice versa. Moving from the lowest CHI score in our sample to the highest was equivalent to a reduction of ∼6% in the prevalence of lameness. There was, however, substantial variation in the total proportion of lame cows seen in herds with the same CHI score. The CHI model was highly inaccurate when predicting the lameness prevalence on farm, with a concordance r of 0.05. The alternative RHD model, which included 6 independent variables of RHD, was more accurate than the CHI model but still inaccurate with a concordance correlation coefficient of 0.31. Both the CHI and the alternative RHD models were unsuitable for accurately predicting the prevalence of lameness on farm. Whereas their constituent parts were reflective of claw health at the herd level, they failed to reflect the complex, multifactorial nature of lameness in dairy herds. The CHI may still be useful for claw health management, as a tool for identifying potential issues on farm, and motivating producer engagement but further investigation is required. The RHD variables in the alternative model are simpler and more widely available than the CHI, facilitating replication and further development in other countries or groups of dairy herds outside of Norway.
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来源期刊
Journal of Dairy Science
Journal of Dairy Science 农林科学-奶制品与动物科学
CiteScore
7.90
自引率
17.10%
发文量
784
审稿时长
4.2 months
期刊介绍: The official journal of the American Dairy Science Association®, Journal of Dairy Science® (JDS) is the leading peer-reviewed general dairy research journal in the world. JDS readers represent education, industry, and government agencies in more than 70 countries with interests in biochemistry, breeding, economics, engineering, environment, food science, genetics, microbiology, nutrition, pathology, physiology, processing, public health, quality assurance, and sanitation.
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