Literature DB >> 28294092

Genetic parameters of Visual Image Analysis primal cut carcass traits of commercial prime beef slaughter animals.

K L Moore1, R Mrode1, M P Coffey1.   

Abstract

Visual Image analysis (VIA) of carcass traits provides the opportunity to estimate carcass primal cut yields on large numbers of slaughter animals. This allows carcases to be better differentiated and farmers to be paid based on the primal cut yields. It also creates more accurate genetic selection due to high volumes of data which enables breeders to breed cattle that better meet the abattoir specifications and market requirements. In order to implement genetic evaluations for VIA primal cut yields, genetic parameters must first be estimated and that was the aim of this study. Slaughter records from the UK prime slaughter population for VIA carcass traits was available from two processing plants. After edits, there were 17 765 VIA carcass records for six primal cut traits, carcass weight as well as the EUROP conformation and fat class grades. Heritability estimates after traits were adjusted for age ranged from 0.32 (0.03) for EUROP fat to 0.46 (0.03) for VIA Topside primal cut yield. Adjusting the VIA primal cut yields for carcass weight reduced the heritability estimates, with estimates of primal cut yields ranging from 0.23 (0.03) for Fillet to 0.29 (0.03) for Knuckle. Genetic correlations between VIA primal cut yields adjusted for carcass weight were very strong, ranging from 0.40 (0.06) between Fillet and Striploin to 0.92 (0.02) between Topside and Silverside. EUROP conformation was also positively correlated with the VIA primal cuts with genetic correlation estimates ranging from 0.59 to 0.84, whereas EUROP fat was estimated to have moderate negative correlations with primal cut yields, estimates ranged from -0.11 to -0.46. Based on these genetic parameter estimates, genetic evaluation of VIA primal cut yields can be undertaken to allow the UK beef industry to select carcases that better meet abattoir specification and market requirements.

Entities:  

Keywords:  Visual Image Analysis (VIA); carcass traits; genetic parameter estimation; prime slaughter beef cattle

Mesh:

Year:  2017        PMID: 28294092     DOI: 10.1017/S1751731117000489

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


  5 in total

1.  Integrating the RFID identification system for Charolaise breeding bulls with 3D imaging for virtual archive creation.

Authors:  Maria Grazia Cappai; Filippo Gambella; Davide Piccirilli; Nicola Graziano Rubiu; Corrado Dimauro; Antonio Luigi Pazzona; Walter Pinna
Journal:  PeerJ Comput Sci       Date:  2019-03-04

2.  Influence of Production Factors on Beef Primal Tissue Composition.

Authors:  Vipasha Sood; Argenis Rodas-González; Stephanie Lam; Óscar López-Campos; Jose Segura; Timothy Schwinghamer; Michael Dugan; John Basarab; Jennifer Aalhus; Manuel Juárez
Journal:  Foods       Date:  2022-02-11

3.  Estimating genetics of body dimensions and activity levels in pigs using automated pose estimation.

Authors:  Wim Gorssen; Carmen Winters; Roel Meyermans; Rudi D'Hooge; Steven Janssens; Nadine Buys
Journal:  Sci Rep       Date:  2022-09-13       Impact factor: 4.996

Review 4.  Image Analysis and Computer Vision Applications in Animal Sciences: An Overview.

Authors:  Arthur Francisco Araújo Fernandes; João Ricardo Rebouças Dórea; Guilherme Jordão de Magalhães Rosa
Journal:  Front Vet Sci       Date:  2020-10-21

5.  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

  5 in total

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