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Updated: Jul 1, 2026

Instrumentation of Near-term Fetal Sheep for Multivariate Chronic Non-anesthetized Recordings
Published on: October 25, 2015
CT scanning technology to asses the genetic and phenotypic correlations, and selection potential of carcass traits in
Yuan Zhao1, Guoxing Jia2, Xiaoxue Zhang2
1State Key Laboratory of Herbage Improvement and Grassland Agro- Ecosystems, 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, Lanzhou, China.
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.
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