Kim, Eun Ho
(Department of Animal Science, Gyeongsang National University)
,
Kim, Hyeon Kwon
(Institute of Agriculture and Life Science, Gyeongsang National University)
,
Sun, Du Won
(Department of Animal Science and Biotechnology, Gyeongsang National University)
,
Kang, Ho Chan
(Institute of Agriculture and Life Science, Gyeongsang National University)
,
Lee, Doo Ho
(Department of Animal Science and Biotechnology, Chungnam National University)
,
Lee, Seung Hwan
(Department of Animal Science and Biotechnology, Chungnam National University)
,
Lee, Jae Bong
(Korea Zoonosis Research Institute (KoZRI), Chonbuk National University)
,
Lim, Hyun Tae
(Department of Animal Science, Gyeongsang National University)
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 thicknes...
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 ㎠ to 2.466 ㎠, 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.
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 ㎠ to 2.466 ㎠, 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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제안 방법
From bulls that were raised with the same breeding management, the performance test selects candidate bulls through growth report verification while the progeny test selects a Korean proven bull’s number (KPN) through verifying the growth and carcass grade of the candidate bull’s progeny [2].
If this is used for elite cow selection and Hanwoo improvement, the problem of inbreeding can be solved through securing a large number of genetic diversity and it can increase the profitability of farms and have improvement effect as the reproduction through elite cows becomes possible, instead of elite calf production through specific KPN. Therefore, this study analyzed the EBV and accuracy using the pedigree information of Hanwoo cows in Gyeongnam to construct basic data for the selection of elite cows.
In the farms, the connection points with the reference group increase with higher pedigree relationship of an individual, which enables accurate relationship coefficient analysis. Through this, it is seen that the heritability and accuracy were estimated higher than previous studies because of the lowered residual variance of each trait and high relationship coefficient for the EBV and the degree of accuracy analyzed in this study.
대상 데이터
For the test group, 34,705 individual identification numbers of Korean cattle born in the Gyeongnam collected from 2003 to 2017 year was provided by GAST, the university enterprise of Gyeongsang National University. The sex, region, birth year and pedigree were collected by searching the individual identification number through the KAPE and KAIA.
The pedigree collection was done in the same way as the previous test group’s pedigree construction method, and a total of 1,270,300 heads pedigree were constructed.
The pedigree of the test and the reference groups were combined to remove duplicate individuals using the R program, and ultimately, pedigree for 1,309,511 heads were constructed and used for analysis. Pedigree and phenotype were used to estimate the EBV, prediction error variance (PEV), genetic parameters, and genetic correlation for each trait and the multiple trait animal model of the BLUPF90 program [6] were used.
The pedigree estimates the relationship coefficient between individuals using the pedigree relationship of the test and reference groups, and it is analyzed with the phenotype to estimate the EBV. The reference group used for the analysis was 545,483 heads slaughtered at an average age of 30 months and it was provided by the KAPE. The pedigree collection was done in the same way as the previous test group’s pedigree construction method, and a total of 1,270,300 heads pedigree were constructed.
The reference group used in this study were 545,483 heads that were slaughtered at an average age of 30 months. The mean and standard deviation for CWT, EMA, BFT, and MS were 431.
이론/모형
1. Mean estimated breeding value (EBV) by birth year according to traits of test population using best linear unbiased prediction (BLUP) method. CWT, carcass weight; EMA, eye muscle area; BFT, backfat thickness; MS, marbling score; APT, animal products traceability.
The pedigree of the test and the reference groups were combined to remove duplicate individuals using the R program, and ultimately, pedigree for 1,309,511 heads were constructed and used for analysis. Pedigree and phenotype were used to estimate the EBV, prediction error variance (PEV), genetic parameters, and genetic correlation for each trait and the multiple trait animal model of the BLUPF90 program [6] were used. For the fixed effect, the birth year, birth month and age at slaughter were used, and the mixed model equation is as follows [7].
성능/효과
It can be confirmed that the EBV of the cow group born between 2010 to 2017 improved to 9.885 kg, 2.466 cm2, −0.357 mm, and 0.559 points.
The degree of accuracy of CWT, EMA, BFT, and MS estimated in this study were 0.559, 0.551, 0.554, and 0.558, respectively. Looking at previous studies, Lee et al.
The selected KPN supplies semen to farms across the country to lead the improvement of Hanwoo but selecting less than 30 bulls per year for new KPN selection to improve Hanwoo reduces the genetic diversity of Hanwoo and farmer’s preference for specific KPN has become a factor for the rise of the inbreeding coefficient.
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