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Estimation of Genetic Parameters for Growth Traits in Yorkshire  

Song, Kwang-Lim (Division of Applied Life Science(Insti. of Agric. & Life Sci.) Gyeongsang National Univ.)
Kim, Byeong-Woo (Division of Applied Life Science(Insti. of Agric. & Life Sci.) Gyeongsang National Univ.)
Roh, Seung-Hee (Hanwoo Improvement Center NACF)
Sun, Du-Won (Division of Applied Life Science(Insti. of Agric. & Life Sci.) Gyeongsang National Univ.)
Kim, Hyo-Sun (National Institute of Animal Science, R.D.A.)
Lee, Deuk-Hwan (Hankyong National University)
Jeon, Jin-Tae (Division of Applied Life Science(Insti. of Agric. & Life Sci.) Gyeongsang National Univ.)
Lee, Jung-Gyu (Division of Applied Life Science(Insti. of Agric. & Life Sci.) Gyeongsang National Univ.)
Publication Information
Journal of agriculture & life science / v.44, no.3, 2010 , pp. 41-52 More about this Journal
Abstract
This study was conducted to estimate genetic parameters for growth traits using multivariate animal models in Yorkshire breed. For the study, 16,202 records for growth traits collected between the year 1999 and 2005 from Yorkshire pigs in K GGP were used. The effects of environmental factors such as sex, birth year, birth season, parity and birth weight group affected growth traits significantly (p<0.01). Birth weight tended to be positively correlated with average daily gain (ADG) and lean percent. But it seemed to affect age at 90 kg, average adjusted backfat thickness (BF), and eye muscle ares (EMA) negatively. For average pig suckling weight (ASW) and total weight at suckling (TWS), the higher birth weight is the better performance. But, in case of total number of born and number of suckling, the result was shown vice versa. Approximately 10~30% lower heritability estimates were obtained for growth traits by using the model that includes descriptions of common litter effects (CL) than by using the model that ignores those (NCL) for more accurate estimation of heritability. The estimates of heritabilities were 0.468, and 0.328 for ADG, 0.474 and 0.326 for age at 90 kg, 0.452, and 0.396 for BF, 0.240 and 0.200 for EMA and, 0.458, and 0.380 for lean percent in NCL and CL, respectively. Therefore, in order to estimate optimal genetic parameters, it could be inferred that the statistical model which considers litter effects must be applied.
Keywords
Growth Traits; Genetic parameter; Heritability; Genetic Correlation; Swine;
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