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Monitoring bovine dairy calf health and related risk factors in the first three months of rearing. | LitMetric

Monitoring bovine dairy calf health and related risk factors in the first three months of rearing.

Acta Vet Scand

Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Grønnegårdsvej 8, DK-1870, Frederiksberg C, Denmark.

Published: October 2023

AI Article Synopsis

  • - Rearing replacement heifers in the dairy industry is crucial but costly due to high disease susceptibility in preweaned calves, necessitating systematic health monitoring to ensure animal welfare and reduce management costs.
  • - A study developed a health-monitoring tool for dairy calves, involving clinical observations and diagnostic tests at three different ages; it included data from 77 calves across nine Danish herds, assessing their immunization and health status.
  • - Results highlighted significant health concerns, such as 31% of calves experiencing passive transfer failure, and varying clinical signs of gastrointestinal and respiratory diseases over time, indicating the need for tailored herd-specific health monitoring strategies.

Article Abstract

Background: Rearing replacement heifers is pivotal for the dairy industry and is associated with high input costs for the preweaned calves, due to their higher susceptibility to diseases. Ensuring calf health and viability calls for systematic approaches in order to mitigate the costs induced by managing sick calves and to ensure animal welfare. The objective of this study was to develop a systematic and feasible health-monitoring tool for bovine dairy calves based on repeated clinical observations and diagnostic results of calves at three time points; the 1st (T0), the 3rd (T1) and the 12th (T3) week of age. The study included observations from 77 dairy heifer calves in nine Danish commercial dairy herds. Immunisation status was assessed by serum Brix% at T0. Clinical scoring included gastrointestinal disease (GD) and respiratory disease (RD). The average daily weight gain (ADWG) was estimated from heart-girth measurements. Pathogen detection from nasal swabs and faecal samples were analysed for 16 respiratory and enteric pathogens by means of high-throughput real time-PCR. All measures obtained in each herd were visualised in a panel to follow the health status of each calf over time.

Results: The individual clinical observations combined with diagnostic information from immunisation and pathogen detection form each enrolled calf are presented in a herd dashboard illustrating the health status over the study period. This monitoring revealed failure of passive transfer (Brix% < 8.1) in 31% of the 77 enrolled calves, signs of severe GD peaked at T0 with 20% affected calves, while signs of severe RD peaked at T2 with 42% affected calves. ADWG over the first eight weeks was estimated to be 760 g (± 190 g). Pathogen profiles varied between herds.

Conclusions: The large variation in both clinical disease and pathogen occurrence across herds emphasizes the need for herd specific monitoring. Combining the results of the present study from measures of immunisation, health and growth from individual calves in one visualisation panel allowed for the detection of patterns across age groups in the specific herds, showing promising potential for early detection and interventions that can lead to enhanced calf health and welfare.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10571325PMC
http://dx.doi.org/10.1186/s13028-023-00708-8DOI Listing

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