Animal Bioscience

Asian Australasian Association of Animal Production Societies (아세아태평양축산학회)
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CT scanning technology to asses the genetic and phenotypic correlations, and selection potential of carcass traits in mutton sheep

  • Yuan Zhao (State Key Laboratory of Herbage Improvement and Grassland AgroEcosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University) ;
  • Guoxing Jia (College of Animal Science and Technology, Gansu Agricultural University) ;
  • Xiaoxue Zhang (College of Animal Science and Technology, Gansu Agricultural University) ;
  • Huibin Tian (State Key Laboratory of Herbage Improvement and Grassland AgroEcosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University) ;
  • Deyin Zhang (State Key Laboratory of Herbage Improvement and Grassland AgroEcosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University) ;
  • Yukun Zhang (State Key Laboratory of Herbage Improvement and Grassland AgroEcosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University) ;
  • Xiaolong Li (State Key Laboratory of Herbage Improvement and Grassland AgroEcosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University) ;
  • Jiangbo Cheng (State Key Laboratory of Herbage Improvement and Grassland AgroEcosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University) ;
  • Liming Zhao (State Key Laboratory of Herbage Improvement and Grassland AgroEcosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University) ;
  • Quanzhong Xu (State Key Laboratory of Herbage Improvement and Grassland AgroEcosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University) ;
  • Xiaobin Yang (State Key Laboratory of Herbage Improvement and Grassland AgroEcosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University) ;
  • Zongwu Ma (State Key Laboratory of Herbage Improvement and Grassland AgroEcosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University) ;
  • Dan Xu (State Key Laboratory of Herbage Improvement and Grassland AgroEcosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University) ;
  • Fadi Li (State Key Laboratory of Herbage Improvement and Grassland AgroEcosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University) ;
  • Weimin Wang (State Key Laboratory of Herbage Improvement and Grassland AgroEcosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University)
  • Received : 2025.07.08
  • Accepted : 2025.11.25
  • Published : 2026.06.01
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Abstract

Objective: This study aims to evaluate the variations in carcass fat percentage (CFP), carcass muscle percentage (CMP), carcass bone percentage (CBP), meat-to-bone ratio, carcass weight, loin eye area (REA), backfat thickness (BF), the total tissue depth of muscle and fat at the twelfth rib, 110 mm from the midline (GR), and dressing percentage in 574 mutton sheep using CT scanning technology. It also seeks to estimate the genetic and phenotypic correlations, as well as estimated genomic selection accuracy provides reference for breeding of mutton sheep carcasses. Methods: Phenotypic data from National Mutton Sheep Testing Station; uniform rearing for 155 days. CT scans were used to obtain body images of the sheep, and CT-Calc2012 software was employed to trait determination. Genomic data were sequenced using second-generation sequencing, and SNP calling was performed with GATK. A mixed linear model incorporating both genomic and pedigree data was used to estimate genetic parameters for various traits. Cross-validation through ten-fold was conducted to assess genomic selection accuracy, and both direct and correlated selection responses for carcass traits were analyzed. Results: The coefficient of variation for each trait ranging from 8.86% to 25.12%. All carcass composition traits demonstrated medium to high heritability (0.38-0.51). A strong genetic correlation was found between BF, REA, CFP, and CMP. The genomic selection accuracy for carcass traits ranged from 0.29 to 0.43, suggesting potential for genomic selection in mutton sheep breeding. The genetic progress of CMP and CFP after direct and indirect selection was tested, showing that indirect improvement of CMP and CFP was most significant when selecting for BF and REA. Conclusion: The study indicates that BF and REA are valuable traits for improving carcass composition in mutton sheep breeding, with genomic selection offering prospects for breeding carcass traits more effectively.

Keywords

Acknowledgement

This work was supported by the National Key Research and Development Program of China (2023YFF1001000), Gansu Provincial Department of Education: 2025 Graduate Innovation Star Project (2025CXZX-065), the Gansu Provincial Science and Technology Plan Project (24CXGH007), the Gansu Provincial Science and Technology Plan Project (25CXGH008), and the Gansu Provincial Science and Technology Plan Project (25YFNA017).

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