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KMID : 1025520200620040429
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Journal of Animal Science and Technology
2020 Volume.62 No. 4 p.429 ~ p.437
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The study on estimated breeding value and accuracy for economic traits in Gyoungnam Hanwoo cow (Korean cattle)
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Kim Eun-Ho
Kim Hyeon-Kwon
Sun Du-Won
Kang Ho-Chan
Lee Doo-Ho
Lee Seung-Hwan
Lee Jae-Bong
Lim Hyun-Tae
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Abstract
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This study was conducted to construct basic data for the selection of elite cows by analyzing the estimated breeding value (EBV) and accuracy using the pedigree of Hanwoo cows in Gyeongnam. The phenotype trait used in the analysis are the carcass weight (CWT), eye muscle area (EMA), backfat thickness (BFT) and marbling score (MS). The pedigree of the test group and reference group was collected to build a pedigree structure and a numeric relationship matrix (NRM). The EBV, genetic parameters and accuracy were estimated by applying NRM to the best linear unbiased prediction (BLUP) multiple-trait animal model of the BLUPF90 program. Looking at the pedigree structure of the test group, there were a total of 2,371 cows born between 2003 to 2009, of these 603 cows had basic registration (25%), 562 cows had pedigree registration (24%) and 1,206 cows had advanced registration (51%). The proportion of pedigree registered cows was relatively low but it gradually increased and reached a point of 20,847 cows (68%) between 2010 to 2017. Looking at the change in the EBV, the CWT improved from 4.992 kg to 9.885 kg, the EMA from 0.970 cm2 to 2.466 cm2, the BFT from ?0.186 mm to ?0.357 mm, and the MS from 0.328 to 0.559 points. As a result of genetic parameter estimation, the heritability of CWT, EMA, BFT, and MS were 0.587, 0.416, 0.476, and 0.571, respectively, and the accuracy of those were estimated to be 0.559, 0.551, 0.554, and 0.558, respectively. Selection of superior genetic breed and efficient improvement could be possible if cow ability verification is implemented by using the accurate pedigree of each individual in the farms.
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KEYWORD
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Selection, Pedigree, Estimated breeding value, Accuracy, Elite calf
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