Literature DB >> 22440411

Genetic variation in wholesale carcass cuts predicted from digital images 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 variation in carcass cuts predicted using digital image analysis in commercial cross-bred cattle. The data set comprised 38,404 steers and 14,318 heifers from commercial Irish herds. The traits investigated included the weights of lower value cuts (LVC), medium value cuts (MVC), high value cuts (HVC), very high value cuts (VHVC) and total meat weight. In addition, the weights of total fat and total bones were available on the steers. Heritability of carcass cut weights, within gender, was estimated using an animal linear model, whereas genetic and phenotypic correlations among cuts were estimated using a sire linear model. Carcass weight was included as a covariate in all models. In the steers, heritability ranged from 0.13 (s.e. = 0.02) for VHVC to 0.49 (s.e. = 0.03) for total bone weight, and in the heifers heritability ranged from 0.15 (s.e. = 0.04) for MVC to 0.72 (s.e. = 0.06) for total meat weight. The coefficient of genetic variation for the different cuts varied from 1.4% to 3.6%. Genetic correlations between the different cut weights were all positive and ranged from 0.45 (s.e. = 0.08) to 0.89 (s.e. = 0.03) in the steers, and from 0.47 (s.e. = 0.14) to 0.82 (s.e. = 0.06) in the heifers. Genetic correlations between the wholesale cut weights and carcass conformation ranged from 0.32 (s.e. = 0.06) to 0.45 (s.e. = 0.07) in the steers, and from 0.10 (s.e. = 0.12) to 0.38 (s.e. = 0.09) in the heifers. Genetic correlations between the same wholesale cut traits in steers and heifers ranged from 0.54 (s.e. = 0.14) for MVC to 0.79 (s.e. = 0.06) for total meat weight; genetic correlations between carcass weight and carcass classification for conformation and fat score in both genders varied from 0.80 to 0.87. The existence of genetic variation in carcass cut traits, coupled with the routine availability of predicted cut weights from digital image analysis, clearly shows the potential to genetically improve carcass value.

Entities:  

Year:  2011        PMID: 22440411     DOI: 10.1017/S1751731111000917

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


  6 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.  The achievement of a given carcass specification is under moderate genetic control in cattle.

Authors:  David Kenny; Michelle M Judge; Roy D Sleator; Craig P Murphy; Ross D Evans; Donagh P Berry
Journal:  J Anim Sci       Date:  2020-06-01       Impact factor: 3.159

3.  Animal-level factors associated with the achievement of desirable specifications in Irish beef carcasses graded using the EUROP classification system.

Authors:  David Kenny; Craig P Murphy; Roy D Sleator; Michelle M Judge; Ross D Evans; Donagh P Berry
Journal:  J Anim Sci       Date:  2020-07-01       Impact factor: 3.159

4.  Dressing percentage and the differential between live weight and carcass weight in cattle are influenced by both genetic and non-genetic factors1.

Authors:  Jessica M Coyne; Ross D Evans; Donagh P Berry
Journal:  J Anim Sci       Date:  2019-04-03       Impact factor: 3.159

5.  Validation of a beef cattle maternal breeding objective based on a cross-sectional analysis of a large national cattle database.

Authors:  Alan J Twomey; Andrew R Cromie; Noirin McHugh; Donagh P Berry
Journal:  J Anim Sci       Date:  2020-11-01       Impact factor: 3.159

6.  Evaluation of Genome-Enabled Prediction for Carcass Primal Cut Yields Using Single-Step Genomic Best Linear Unbiased Prediction in Hanwoo Cattle.

Authors:  Masoumeh Naserkheil; Hossein Mehrban; Deukmin Lee; Mi Na Park
Journal:  Genes (Basel)       Date:  2021-11-25       Impact factor: 4.096

  6 in total

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