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A systematic approach to analyse the impact of farm-profiles on bovine health

In this study we present systematic framework to analyse the impact of farm profiles as combinations of environmental conditions and management practices on common diseases in dairy cattle. The data used for this secondary data analysis includes observational data from 166 farms with a total of 5828...

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Autores principales: Matzhold, Caspar, Lasser, Jana, Egger-Danner, Christa, Fuerst-Waltl, Birgit, Wittek, Thomas, Kofler, Johann, Steininger, Franz, Klimek, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8551198/
https://www.ncbi.nlm.nih.gov/pubmed/34707145
http://dx.doi.org/10.1038/s41598-021-00469-2
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author Matzhold, Caspar
Lasser, Jana
Egger-Danner, Christa
Fuerst-Waltl, Birgit
Wittek, Thomas
Kofler, Johann
Steininger, Franz
Klimek, Peter
author_facet Matzhold, Caspar
Lasser, Jana
Egger-Danner, Christa
Fuerst-Waltl, Birgit
Wittek, Thomas
Kofler, Johann
Steininger, Franz
Klimek, Peter
author_sort Matzhold, Caspar
collection PubMed
description In this study we present systematic framework to analyse the impact of farm profiles as combinations of environmental conditions and management practices on common diseases in dairy cattle. The data used for this secondary data analysis includes observational data from 166 farms with a total of 5828 dairy cows. Each farm is characterised by features from five categories: husbandry, feeding, environmental conditions, housing, and milking systems. We combine dimension reduction with clustering techniques to identify groups of similar farm attributes, which we refer to as farm profiles. A statistical analysis of the farm profiles and their related disease risks is carried out to study the associations between disease risk, farm membership to a specific cluster as well as variables that characterise a given cluster by means of a multivariate regression model. The disease risks of five different farm profiles arise as the result of complex interactions between environmental conditions and farm management practices. We confirm previously documented relationships between diseases, feeding and husbandry. Furthermore, novel associations between housing and milking systems and specific disorders like lameness and ketosis have been discovered. Our approach contributes to paving a way towards a more holistic and data-driven understanding of bovine health and its risk factors.
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spelling pubmed-85511982021-10-28 A systematic approach to analyse the impact of farm-profiles on bovine health Matzhold, Caspar Lasser, Jana Egger-Danner, Christa Fuerst-Waltl, Birgit Wittek, Thomas Kofler, Johann Steininger, Franz Klimek, Peter Sci Rep Article In this study we present systematic framework to analyse the impact of farm profiles as combinations of environmental conditions and management practices on common diseases in dairy cattle. The data used for this secondary data analysis includes observational data from 166 farms with a total of 5828 dairy cows. Each farm is characterised by features from five categories: husbandry, feeding, environmental conditions, housing, and milking systems. We combine dimension reduction with clustering techniques to identify groups of similar farm attributes, which we refer to as farm profiles. A statistical analysis of the farm profiles and their related disease risks is carried out to study the associations between disease risk, farm membership to a specific cluster as well as variables that characterise a given cluster by means of a multivariate regression model. The disease risks of five different farm profiles arise as the result of complex interactions between environmental conditions and farm management practices. We confirm previously documented relationships between diseases, feeding and husbandry. Furthermore, novel associations between housing and milking systems and specific disorders like lameness and ketosis have been discovered. Our approach contributes to paving a way towards a more holistic and data-driven understanding of bovine health and its risk factors. Nature Publishing Group UK 2021-10-27 /pmc/articles/PMC8551198/ /pubmed/34707145 http://dx.doi.org/10.1038/s41598-021-00469-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Matzhold, Caspar
Lasser, Jana
Egger-Danner, Christa
Fuerst-Waltl, Birgit
Wittek, Thomas
Kofler, Johann
Steininger, Franz
Klimek, Peter
A systematic approach to analyse the impact of farm-profiles on bovine health
title A systematic approach to analyse the impact of farm-profiles on bovine health
title_full A systematic approach to analyse the impact of farm-profiles on bovine health
title_fullStr A systematic approach to analyse the impact of farm-profiles on bovine health
title_full_unstemmed A systematic approach to analyse the impact of farm-profiles on bovine health
title_short A systematic approach to analyse the impact of farm-profiles on bovine health
title_sort systematic approach to analyse the impact of farm-profiles on bovine health
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8551198/
https://www.ncbi.nlm.nih.gov/pubmed/34707145
http://dx.doi.org/10.1038/s41598-021-00469-2
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