Literature DB >> 28515004

Animal breeding strategies can improve meat quality attributes within entire populations.

D P Berry1, S Conroy2, T Pabiou2, A R Cromie2.   

Abstract

The contribution of animal breeding to changes in animal performance is well documented across a range of species. Once genetic variation in a trait exists, then breeding to improve the characteristics of that trait is possible, if so desired. Considerable genetic variation exists in a range of meat quality attributes across a range of species. The genetic variation that exists for meat quality is as large as observed for most performance traits; thus, within a well-structured breeding program, rapid genetic gain for meat quality could be possible. The rate of genetic gain can be augmented through the integration of DNA-based technologies into the breeding program; such DNA-based technologies should, however, be based on thousands of DNA markers dispersed across the entire genome. Genetic and genomic technologies can also have beneficial impact outside the farm gate as a tool to segregate carcasses or meat cuts based on expected meat quality features.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Keywords:  Cattle; Genetic; Genomic; Pig; Poultry; Sheep

Mesh:

Year:  2017        PMID: 28515004     DOI: 10.1016/j.meatsci.2017.04.019

Source DB:  PubMed          Journal:  Meat Sci        ISSN: 0309-1740            Impact factor:   5.209


  5 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.  Linear classification scores in beef cattle as predictors of genetic merit for individual carcass primal cut yields1.

Authors:  Donagh P Berry; Thierry Pabiou; Rory Fanning; Ross D Evans; Michelle M Judge
Journal:  J Anim Sci       Date:  2019-05-30       Impact factor: 3.159

3.  Dietary Meat Categories and Descriptions in Chronic Disease Research Are Substantively Different within and between Experimental and Observational Studies: A Systematic Review and Landscape Analysis.

Authors:  Lauren E O'Connor; Cody L Gifford; Dale R Woerner; Julia L Sharp; Keith E Belk; Wayne W Campbell
Journal:  Adv Nutr       Date:  2020-01-01       Impact factor: 8.701

4.  Blood Transcriptome Analysis of Beef Cow with Different Parity Revealed Candidate Genes and Gene Networks Regulating the Postpartum Diseases.

Authors:  Yanda Yang; Chencheng Chang; Batu Baiyin; Zaixia Liu; Lili Guo; Le Zhou; Bin Liu; Caixia Shi; Wenguang Zhang
Journal:  Genes (Basel)       Date:  2022-09-19       Impact factor: 4.141

5.  IoT-Blockchain Enabled Optimized Provenance System for Food Industry 4.0 Using Advanced Deep Learning.

Authors:  Prince Waqas Khan; Yung-Cheol Byun; Namje Park
Journal:  Sensors (Basel)       Date:  2020-05-25       Impact factor: 3.576

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.