Literature DB >> 22717237

Genetic relationships between carcass cut weights predicted from video image analysis and other performance traits in cattle.

T Pabiou1, W F Fikse, P R Amer, A R Cromie, A Näsholm, D P Berry.   

Abstract

The objective of this study was to quantify the genetic associations between a range of carcass-related traits including wholesale cut weights predicted from video image analysis (VIA) technology, and a range of pre-slaughter performance traits in commercial Irish cattle. Predicted carcass cut weights comprised of cut weights based on retail value: lower value cuts (LVC), medium value cuts (MVC), high value cuts (HVC) and very high value cuts (VHVC), as well as total meat, fat and bone weights. Four main sources of data were used in the genetic analyses: price data of live animals collected from livestock auctions, live-weight data and linear type collected from both commercial and pedigree farms as well as from livestock auctions and weanling quality recorded on-farm. Heritability of carcass cut weights ranged from 0.21 to 0.39. Genetic correlations between the cut traits and the other performance traits were estimated using a series of bivariate sire linear mixed models where carcass cut weights were phenotypically adjusted to a constant carcass weight. Strongest positive genetic correlations were obtained between predicted carcass cut weights and carcass value (min r g(MVC) = 0.35; max r(g(VHVC)) = 0.69), and animal price at both weaning (min r(g(MVC)) = 0.37; max r(g(VHVC)) = 0.66) and post weaning (min r(g(MVC)) = 0.50; max r(g(VHVC)) = 0.67). Moderate genetic correlations were obtained between carcass cut weights and calf price (min r g(HVC) = 0.34; max r g(LVC) = 0.45), weanling quality (min r(g(MVC)) = 0.12; max r (g(VHVC)) = 0.49), linear scores for muscularity at both weaning (hindquarter development: min r(g(MVC)) = -0.06; max r(g(VHVC)) = 0.46), post weaning (hindquarter development: min r(g(MVC)) = 0.23; max r(g(VHVC)) = 0.44). The genetic correlations between total meat weight were consistent with those observed with the predicted wholesale cut weights. Total fat and total bone weights were generally negatively correlated with carcass value, auction prices and weanling quality. Total bone weight was, however, positively correlated with skeletal scores at weaning and post weaning. These results indicate that some traits collected early in life are moderate-to-strongly correlated with carcass cut weights predicted from VIA technology. This information can be used to improve the accuracy of selection for carcass cut weights in national genetic evaluations.

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Year:  2012        PMID: 22717237     DOI: 10.1017/S1751731112000705

Source DB:  PubMed          Journal:  Animal        ISSN: 1751-7311            Impact factor:   3.240


  7 in total

1.  Potential exists to change, through breeding, the yield of individual primal carcass cuts in cattle without increasing overall carcass weight1.

Authors:  Michelle M Judge; Thierry Pabiou; Jessica Murphy; Stephen B Conroy; P J Hegarty; Donagh P Berry
Journal:  J Anim Sci       Date:  2019-07-02       Impact factor: 3.159

2.  Efficient single-step genomic evaluation for a multibreed beef cattle population having many genotyped animals.

Authors:  E A Mäntysaari; R D Evans; I Strandén
Journal:  J Anim Sci       Date:  2017-11       Impact factor: 3.159

3.  Carcass and efficiency metrics of beef cattle differ by whether the calf was born in a dairy or a beef herd.

Authors:  Alan J Twomey; Siobhán C Ring; Noirin McHugh; Donagh P Berry
Journal:  J Anim Sci       Date:  2020-11-01       Impact factor: 3.159

4.  Whole genome association study identifies regions of the bovine genome and biological pathways involved in carcass trait performance in Holstein-Friesian cattle.

Authors:  Anthony G Doran; Donagh P Berry; Christopher J Creevey
Journal:  BMC Genomics       Date:  2014-10-01       Impact factor: 3.969

5.  Identification of Candidate Variants Associated With Bone Weight Using Whole Genome Sequence in Beef Cattle.

Authors:  Qunhao Niu; Tianliu Zhang; Ling Xu; Tianzhen Wang; Zezhao Wang; Bo Zhu; Xue Gao; Yan Chen; Lupei Zhang; Huijiang Gao; Junya Li; Lingyang Xu
Journal:  Front Genet       Date:  2021-11-29       Impact factor: 4.599

6.  The Association Between Genomic Heterozygosity and Carcass Merit in Cattle.

Authors:  David Kenny; Tara R Carthy; Craig P Murphy; Roy D Sleator; Ross D Evans; Donagh P Berry
Journal:  Front Genet       Date:  2022-02-24       Impact factor: 4.599

7.  Detection of Genomic Imprinting for Carcass Traits in Cattle Using Imputed High-Density Genotype Data.

Authors:  David Kenny; Roy D Sleator; Craig P Murphy; Ross D Evans; Donagh P Berry
Journal:  Front Genet       Date:  2022-07-15       Impact factor: 4.772

  7 in total

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