|BROWN JR, A|
Submitted to: Journal of Animal Science Supplement
Publication Type: Abstract Only
Publication Acceptance Date: 2/15/1999
Publication Date: N/A
Citation: BROWN, A.H., JOHNSON, Z.B., BROWN, M.A., OXFORD, E.L., CAMFIELD, P.K., RAKES, L.Y. EFFECTS OF GENETIC TYPE AND PRODUCTION SYSTEM ON CARCASS TRAITS OF BEEF STEERS. JOURNAL OF ANIMAL SCIENCE SUPPLEMENT. 1999. v. 77(Suppl. 1):165.
Interpretive Summary: Abstract Only.
Technical Abstract: Steers (n=335) of four different known genetic types were managed in two production systems to study differences in carcass traits. Genetic types were large frame-late maturing (LL), intermediate frame-intermediate maturing (II), intermediate frame- early maturing (IE), and small frame-early maturing (SE). Five calves from each genetic type were assigned dto one of two systems in each year of a 9-year study. System I (SI) included management on forage from weaning to slaughter at approximately 20 mo of age, while system II (SII) included management in the feedlot from weaning to slaughter at approximately 14 mo of age. Data collected were shrunk body weight (SBW); hot carcass weight (HCW); chilled carcass weight (CCW); dressing percentage (DRESS); fat thickness at the 12th and 13th rib interface (FAT); percentage kidney, pelvic, and heart fat (KPH); longissimus muscle area (LMA); marbling score (MARB); quality grade (QG); and yield grade (YG). Data were analyzed by least-squares with a linear model including year, genetic type, production system, 2- and 3-way interactions, steer age (linear), and residual error. Least-square means were separated with t-tests. Year and genetic type were significant for all carcass traits. System was a significant source of variation for SBW (P<.10), but not for carcass traits. The genetic type x system interaction was significant (P<.10) for SBW, HCW, CCW, MARB, FAT, and YG. Carcass differences in measures of fatness were greater and more attainable in the feedlot based system which are important using current methods of evaluation. These data indicate that matching genetic type to production systems can increase efficiency of resource use.