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Combinations of non-invasive indicators to detect dairy cows submitted to high-starch-diet challenge
High-starch diets (HSDs) fed to high-producing ruminants are often responsible for rumen dysfunction and could impair animal health and production. Feeding HSDs are often characterized by transient rumen pH depression, accurate monitoring of which requires costly or invasive methods. Numerous clinic...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6974427/ https://www.ncbi.nlm.nih.gov/pubmed/31311612 http://dx.doi.org/10.1017/S1751731119001629 |
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author | Villot, C. Martin, C. Bodin, J. Durand, D. Graulet, B. Ferlay, A. Mialon, M.M. Trevisi, E. Silberberg, M. |
author_facet | Villot, C. Martin, C. Bodin, J. Durand, D. Graulet, B. Ferlay, A. Mialon, M.M. Trevisi, E. Silberberg, M. |
author_sort | Villot, C. |
collection | PubMed |
description | High-starch diets (HSDs) fed to high-producing ruminants are often responsible for rumen dysfunction and could impair animal health and production. Feeding HSDs are often characterized by transient rumen pH depression, accurate monitoring of which requires costly or invasive methods. Numerous clinical signs can be followed to monitor such diet changes but no specific indicator is able to make a statement at animal level on-farm. The aim of this pilot study was to assess a combination of non-invasive indicators in dairy cows able to monitor a HSD in experimental conditions. A longitudinal study was conducted in 11 primiparous dairy cows fed with two different diets during three successive periods: a 4-week control period (P1) with a low-starch diet (LSD; 13% starch), a 4-week period with an HSD (P2, 35% starch) and a 3-week recovery period (P3) again with the LSD. Animal behaviour was monitored throughout the experiment, and faeces, urine, saliva, milk and blood were sampled simultaneously in each animal at least once a week for analysis. A total of 136 variables were screened by successive statistical approaches including: partial least squares-discriminant analysis, multivariate analysis and mixed-effect models. Finally, 16 indicators were selected as the most representative of a HSD challenge. A generalized linear mixed model analysis was applied to highlight parsimonious combinations of indicators able to identify animals under our experimental conditions. Eighteen models were established and the combination of milk urea nitrogen, blood bicarbonate and feed intake was the best to detect the different periods of the challenge with both 100% of specificity and sensitivity. Other indicators such as the number of drinking acts, fat:protein ratio in milk, urine, and faecal pH, were the most frequently used in the proposed models. Finally, the established models highlight the necessity for animals to have more than 1 week of recovery diet to return to their initial control state after a HSD challenge. This pilot study demonstrates the interest of using combinations of non-invasive indicators to monitor feed changes from a LSD to a HSD to dairy cows in order to improve prevention of rumen dysfunction on-farm. However, the adjustment and robustness of the proposed combinations of indicators need to be challenged using a greater number of animals as well as different acidogenic conditions before being applied on-farm. |
format | Online Article Text |
id | pubmed-6974427 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-69744272020-01-31 Combinations of non-invasive indicators to detect dairy cows submitted to high-starch-diet challenge Villot, C. Martin, C. Bodin, J. Durand, D. Graulet, B. Ferlay, A. Mialon, M.M. Trevisi, E. Silberberg, M. Animal Research Article High-starch diets (HSDs) fed to high-producing ruminants are often responsible for rumen dysfunction and could impair animal health and production. Feeding HSDs are often characterized by transient rumen pH depression, accurate monitoring of which requires costly or invasive methods. Numerous clinical signs can be followed to monitor such diet changes but no specific indicator is able to make a statement at animal level on-farm. The aim of this pilot study was to assess a combination of non-invasive indicators in dairy cows able to monitor a HSD in experimental conditions. A longitudinal study was conducted in 11 primiparous dairy cows fed with two different diets during three successive periods: a 4-week control period (P1) with a low-starch diet (LSD; 13% starch), a 4-week period with an HSD (P2, 35% starch) and a 3-week recovery period (P3) again with the LSD. Animal behaviour was monitored throughout the experiment, and faeces, urine, saliva, milk and blood were sampled simultaneously in each animal at least once a week for analysis. A total of 136 variables were screened by successive statistical approaches including: partial least squares-discriminant analysis, multivariate analysis and mixed-effect models. Finally, 16 indicators were selected as the most representative of a HSD challenge. A generalized linear mixed model analysis was applied to highlight parsimonious combinations of indicators able to identify animals under our experimental conditions. Eighteen models were established and the combination of milk urea nitrogen, blood bicarbonate and feed intake was the best to detect the different periods of the challenge with both 100% of specificity and sensitivity. Other indicators such as the number of drinking acts, fat:protein ratio in milk, urine, and faecal pH, were the most frequently used in the proposed models. Finally, the established models highlight the necessity for animals to have more than 1 week of recovery diet to return to their initial control state after a HSD challenge. This pilot study demonstrates the interest of using combinations of non-invasive indicators to monitor feed changes from a LSD to a HSD to dairy cows in order to improve prevention of rumen dysfunction on-farm. However, the adjustment and robustness of the proposed combinations of indicators need to be challenged using a greater number of animals as well as different acidogenic conditions before being applied on-farm. Cambridge University Press 2020-02 2019-07-16 /pmc/articles/PMC6974427/ /pubmed/31311612 http://dx.doi.org/10.1017/S1751731119001629 Text en © The Animal Consortium 2019 http://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 licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work. |
spellingShingle | Research Article Villot, C. Martin, C. Bodin, J. Durand, D. Graulet, B. Ferlay, A. Mialon, M.M. Trevisi, E. Silberberg, M. Combinations of non-invasive indicators to detect dairy cows submitted to high-starch-diet challenge |
title | Combinations of non-invasive indicators to detect dairy cows submitted to high-starch-diet challenge |
title_full | Combinations of non-invasive indicators to detect dairy cows submitted to high-starch-diet challenge |
title_fullStr | Combinations of non-invasive indicators to detect dairy cows submitted to high-starch-diet challenge |
title_full_unstemmed | Combinations of non-invasive indicators to detect dairy cows submitted to high-starch-diet challenge |
title_short | Combinations of non-invasive indicators to detect dairy cows submitted to high-starch-diet challenge |
title_sort | combinations of non-invasive indicators to detect dairy cows submitted to high-starch-diet challenge |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6974427/ https://www.ncbi.nlm.nih.gov/pubmed/31311612 http://dx.doi.org/10.1017/S1751731119001629 |
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