[Relationship between metabolic profiles in herd health and 4 scoring systems used in dairy herd health programs: Statistical analysis with an additive Bayesian network]

[奶牛群健康代谢谱与奶牛群健康计划中使用的4种评分系统之间的关系:基于加性贝叶斯网络的统计分析]

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Abstract

OBJECTIVE: The aim of the present study was to describe the relationship between the biochemical variables used in metabolic profiles and various scores commonly used in herd health management of dairy cows. The Bayesian network was used to determine the relationship between metabolic blood profiles and the scores for body condition (BC), rumen fill (RF), faecal consistency (FC) and undigested fraction (UF) on a herd basis. MATERIALS AND METHODS: In each of 10 dairy herds, blood was collected from a minimum of ten lactating cows for biochemical analysis and generation of metabolic profiles. This yielded a total of 106 blood samples. The biochemical results in the metabolic profiles were stratified by days in milk and compared with the scores of BC, RF, FC and UF using an additive Bayesian network. RESULTS: The blood glucose concentration directly affected the FC score. The was an effect of beta-hydroxybutyrate (BHB) on free fatty acids (FFS). An additional effect of BHB on the concentration of urea was detected. The concentration of urea affected the concentration of phosphorus and GOT activity. Urea concentration also affected the blood concentrations of calcium and subsequently magnesium. Rumen fill had an effect on BC score and liver enzyme activity. Glutathione peroxidase, which is used to assess the levels of selenium in cattle, had no significant relationship with the other variables and was therefore isolated in the model. CONCLUSION: The use of a multidimensional model, which in this study was an additive Bayesian network, showed the relationships between the biochemical variables in the metabolic profiles and the scoring systems commonly used for the management of dairy cow herds. The relationships between the biochemical variables and the four scoring systems can be used to manage dairy herds more effectively. CLINICAL RELEVANCE: The biochemical variables used in metabolic profiles were correlated with health scoring systems commonly used in dairy herds. The latter can be carried out more rapidly and at a lower cost than metabolic profiles. In dairy cows with metabolic diseases or fertility disorders, scoring systems do not replace detailed evaluations that include metabolic profiles.

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