Estimation of Relative Economic Weights of Hanwoo Carcass Traits Based on Carcass Market Price

Autor: Tae Jung Choi, Seung Soo Lee, You Lim Choi, Hyo Sun Kim, Yun Ho Choy, Jae Gwan Choi, Kyung Chul Koh, Byoungho Park, Kwang-Hyun Cho
Jazyk: angličtina
Rok vydání: 2012
Předmět:
Zdroj: Asian-Australasian Journal of Animal Sciences
ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES(25): 12
Asian-Australasian Journal of Animal Sciences, Vol 25, Iss 12, Pp 1667-1673 (2012)
ISSN: 1976-5517
1011-2367
Popis: The objective of this study was to estimate economic weights of Hanwoo carcass traits that can be used to build economic selection indexes for selection of seedstocks. Data from carcass measures for determining beef yield and quality grades were collected and provided by the Korean Institute for Animal Products Quality Evaluation (KAPE). Out of 1,556,971 records, 476,430 records collected from 13 abattoirs from 2008 to 2010 after deletion of outlying observations were used to estimate relative economic weights of bid price per kg carcass weight on cold carcass weight (CW), eye muscle area (EMA), backfat thickness (BF) and marbling score (MS) and the phenotypic relationships among component traits. Price of carcass tended to increase linearly as yield grades or quality grades, in marginal or in combination, increased. Partial regression coefficients for MS, EMA, BF, and for CW in original scales were +948.5 won/score, +27.3 won/cm(2), -95.2 won/mm and +7.3 won/kg when all three sex categories were taken into account. Among four grade determining traits, relative economic weight of MS was the greatest. Variations in partial regression coefficients by sex categories were great but the trends in relative weights for each carcass measures were similar. Relative economic weights of four traits in integer values when standardized measures were fit into covariance model were +4:+1:-1:+1 for MS:EMA:BF:CW. Further research is required to account for the cost of production per unit carcass weight or per unit production under different economic situations.
Databáze: OpenAIRE