↓ Skip to main content

Selection of pigs for improved coping with health and environmental challenges: breeding for resistance or tolerance?

Overview of attention for article published in Frontiers in Genetics, January 2012
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
40 Dimensions

Readers on

mendeley
73 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Selection of pigs for improved coping with health and environmental challenges: breeding for resistance or tolerance?
Published in
Frontiers in Genetics, January 2012
DOI 10.3389/fgene.2012.00281
Pubmed ID
Authors

Sarita Z. Y. Guy, Peter C. Thomson, Susanne Hermesch

Abstract

The benefits of improved health and welfare in pigs have driven refinements in management and selection practices, one of which is the production of pig phenotypes that can maintain health and productivity by improving response against pathogens. Selection has traditionally been made for host resistance; but the alternative host defence mechanism-host tolerance-is now being considered, as breeding for disease tolerance allows maintenance of high performance across environments of increasing pathogenic load. A distinction must be made between these two mechanisms as they vary in their influence on host-pathogen interactions and pathogen evolution, and consequently on the results of breeding programs. Many pig production studies have failed to distinguish between resistance and tolerance; although a distinction may not always be possible. This article reviews current perspectives in selective breeding for disease resistance and tolerance in growing pigs, and the attendant industry implications. To assess the viability of breeding for resistance and/or tolerance for improved response to disease and other environmental challenges, we propose the use of routine farm records, instead of data measurements taken from laboratory experiments. Consequently, a number of factors need to be taken into account simultaneously for a multidimensional modeling approach. This includes not only genotype and disease variables, but also descriptors of the environment, as well as any possible interactions. It may not be feasible to record individual pathogen loads, and therefore true tolerance, on farm using routinely collected data. However, it may be estimated with group (farm) means, or other proxy measures. Although this results in a bias, this may still be useful for modeling and quantifying resistance and tolerance. We can then quantify success of selection, and this may enable us to decide whether to select for disease resistance versus disease tolerance.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 2 3%
United Kingdom 1 1%
Norway 1 1%
Canada 1 1%
Unknown 68 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 22%
Researcher 16 22%
Student > Master 12 16%
Student > Bachelor 5 7%
Student > Doctoral Student 4 5%
Other 9 12%
Unknown 11 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 42 58%
Biochemistry, Genetics and Molecular Biology 4 5%
Veterinary Science and Veterinary Medicine 3 4%
Social Sciences 3 4%
Unspecified 2 3%
Other 6 8%
Unknown 13 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 17 December 2012.
All research outputs
#21,767,301
of 24,290,096 outputs
Outputs from Frontiers in Genetics
#9,264
of 13,052 outputs
Outputs of similar age
#229,027
of 251,740 outputs
Outputs of similar age from Frontiers in Genetics
#194
of 255 outputs
Altmetric has tracked 24,290,096 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,052 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 251,740 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 255 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.