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Reproductive management in dairy cows - the future

Overview of attention for article published in Irish Veterinary Journal, January 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#19 of 257)
  • High Attention Score compared to outputs of the same age (84th percentile)

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1 news outlet
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2 X users

Citations

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76 Dimensions

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350 Mendeley
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Title
Reproductive management in dairy cows - the future
Published in
Irish Veterinary Journal, January 2018
DOI 10.1186/s13620-017-0112-y
Pubmed ID
Authors

Mark A. Crowe, Miel Hostens, Geert Opsomer

Abstract

Drivers of change in dairy herd health management include the significant increase in herd/farm size, quota removal (within Europe) and the increase in technologies to aid in dairy cow reproductive management. There are a number of key areas for improving fertility management these include: i) handling of substantial volumes of data, ii) genetic selection (including improved phenotypes for use in breeding programmes), iii) nutritional management (including transition cow management), iv) control of infectious disease, v) reproductive management (and automated systems to improve reproductive management), vi) ovulation / oestrous synchronisation, vii) rapid diagnostics of reproductive status, and viii) management of male fertility. This review covers the current status and future outlook of many of these key factors that contribute to dairy cow herd health and reproductive performance. In addition to improvements in genetic trends for fertility, numerous other future developments are likely in the near future. These include: i) development of new and novel fertility phenotypes that may be measurable in milk; ii) specific fertility genomic markers; iii) earlier and rapid pregnancy detection; iv) increased use of activity monitors; v) improved breeding protocols; vi) automated inline sensors for relevant phenotypes that become more affordable for farmers; and vii) capturing and mining multiple sources of "Big Data" available to dairy farmers. These should facilitate improved performance, health and fertility of dairy cows in the future.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 350 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 350 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 51 15%
Student > Master 49 14%
Student > Ph. D. Student 32 9%
Researcher 31 9%
Other 11 3%
Other 51 15%
Unknown 125 36%
Readers by discipline Count As %
Agricultural and Biological Sciences 87 25%
Veterinary Science and Veterinary Medicine 73 21%
Biochemistry, Genetics and Molecular Biology 10 3%
Engineering 10 3%
Medicine and Dentistry 9 3%
Other 31 9%
Unknown 130 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 November 2023.
All research outputs
#3,139,860
of 25,382,440 outputs
Outputs from Irish Veterinary Journal
#19
of 257 outputs
Outputs of similar age
#67,459
of 449,895 outputs
Outputs of similar age from Irish Veterinary Journal
#1
of 4 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 257 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one has done particularly well, scoring higher than 92% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 449,895 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them