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논문 기본 정보

자료유형
학술저널
저자정보
Eun Ho Kim (Gyeongsang National University) Du Won Sun (Gyeongsang National University) Ho Chan Kang (Gyeongsang National University) Ji Yeong Kim (Gyeongsang National University) Cheol Hyun Myung (Gyeongsang National University) Doo Ho Lee (Chungnam National University) Seung Hwan Lee (Chungnam National University) Hyun Tae Lim (Gyeongsang National University)
저널정보
충남대학교 농업과학연구소 Korean Journal of Agricultural Science Korean Journal of Agricultural Science Vol.48 No.4
발행연도
2021.12
수록면
681 - 691 (11page)

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The estimated breeding value (EBV) and accuracy of Hanwoo steer (Korean cattle) is an indicator that can predict the slaughter time in the future and carcass performance outcomes. Recently, studies using pedigrees and genotypes are being actively conducted to improve the accuracy of the EBV. In this study, the pedigree and genotype of 46 steers obtained from livestock farm A in Gyeongnam were used for a pedigree best linear unbiased prediction (PBLUP) and a genomic best linear unbiased prediction (GBLUP) to estimate and analyze the breeding value and accuracy of the carcass weight (CWT), eye muscle area (EMA), back-fat thickness (BFT), and marbling score (MS). PBLUP estimated the EBV and accuracy by constructing a numeric relationship matrix (NRM) from the 46 steers and reference population Ⅰ (545,483 heads) with the pedigree and phenotype. GBLUP estimated genomic EBV (GEBV) and accuracy by constructing a genomic relationship matrix (GRM) from the 46 steers and reference population Ⅱ (16,972 heads) with the genotype and phenotype. As a result, in the order of CWT, EMA, BFT, and MS, the accuracy levels of PBLUP were 0.531, 0.519, 0.524 and 0.530, while the accuracy outcomes of GBLUP were 0.799, 0.779, 0.768, and 0.810. The accuracy estimated by GBLUP was 50.1 - 53.1% higher than that estimated by PBLUP. GEBV estimated with the genotype is expected to show higher accuracy than the EBV calculated using only the pedigree and is thus expected to be used as basic data for genomic selection in the future.

목차

Abstract
Introduction
Materials and Methods
Results and Discussion
Conclusion
References

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