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Zusammenhänge zwischen metabolischen Profilen und 4 Bestandsbetreuung-Scores bei Milchkühen: Statistische Analyse anhand eines additiven Bayesian Netzwerkes

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...

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Autores principales: Hässig, Michael, Hanimann, Annina, Lewis, Frazer, Hartnack, Sonja
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Georg Thieme Verlag KG 2023
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10212649/
https://www.ncbi.nlm.nih.gov/pubmed/37230142
http://dx.doi.org/10.1055/a-2061-9990
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author Hässig, Michael
Hanimann, Annina
Lewis, Frazer
Hartnack, Sonja
author_facet Hässig, Michael
Hanimann, Annina
Lewis, Frazer
Hartnack, Sonja
author_sort Hässig, Michael
collection PubMed
description 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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spelling pubmed-102126492023-05-26 Zusammenhänge zwischen metabolischen Profilen und 4 Bestandsbetreuung-Scores bei Milchkühen: Statistische Analyse anhand eines additiven Bayesian Netzwerkes Hässig, Michael Hanimann, Annina Lewis, Frazer Hartnack, Sonja Tierarztl Prax Ausg G Grosstiere Nutztiere 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. Georg Thieme Verlag KG 2023-05-25 /pmc/articles/PMC10212649/ /pubmed/37230142 http://dx.doi.org/10.1055/a-2061-9990 Text en The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/). https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited.
spellingShingle Hässig, Michael
Hanimann, Annina
Lewis, Frazer
Hartnack, Sonja
Zusammenhänge zwischen metabolischen Profilen und 4 Bestandsbetreuung-Scores bei Milchkühen: Statistische Analyse anhand eines additiven Bayesian Netzwerkes
title Zusammenhänge zwischen metabolischen Profilen und 4 Bestandsbetreuung-Scores bei Milchkühen: Statistische Analyse anhand eines additiven Bayesian Netzwerkes
title_full Zusammenhänge zwischen metabolischen Profilen und 4 Bestandsbetreuung-Scores bei Milchkühen: Statistische Analyse anhand eines additiven Bayesian Netzwerkes
title_fullStr Zusammenhänge zwischen metabolischen Profilen und 4 Bestandsbetreuung-Scores bei Milchkühen: Statistische Analyse anhand eines additiven Bayesian Netzwerkes
title_full_unstemmed Zusammenhänge zwischen metabolischen Profilen und 4 Bestandsbetreuung-Scores bei Milchkühen: Statistische Analyse anhand eines additiven Bayesian Netzwerkes
title_short Zusammenhänge zwischen metabolischen Profilen und 4 Bestandsbetreuung-Scores bei Milchkühen: Statistische Analyse anhand eines additiven Bayesian Netzwerkes
title_sort zusammenhänge zwischen metabolischen profilen und 4 bestandsbetreuung-scores bei milchkühen: statistische analyse anhand eines additiven bayesian netzwerkes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10212649/
https://www.ncbi.nlm.nih.gov/pubmed/37230142
http://dx.doi.org/10.1055/a-2061-9990
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