286 Considerations that impact carcass premiums and discounts of commercial cattle.

Abstract The constantly dynamic relationship between carcass value and cost of production drives the specific slaughter endpoint deemed to be the most advantageous to the cattle feeder at a given point in time. The signal to the supply chain utilized by beef processors to convey the desired carcass attributes to meet customer needs predominantly involves grid premiums and discounts. Managing the tails of the carcass attribute distribution within a marketing group is key for business success with grid-based selling. Individual initial and final BW data from approximately 6500 cattle used in 22 controlled studies that were procured through typical auction market channels in groups of approximately 200 to 500 animals displayed an initial BW coefficient of variation (CV) of 6.7% within procurement group (mean = 352 kg, range = 141 kg). Blocking within procurement group by only initial BW reduced the CV of initial BW by 55% (to 3.0%), decreased the range of final BW by 42%, but only slightly decreased the CV of final BW after an average of 147 days before slaughter compared to no sorting being applied. A commercial sorting system (PenPoint™) that utilizes algorithms of current BW and hip height was evaluated using 44 pens containing 8192 steers at a commercial feedyard. Identifying subpopulations resulted in greater net return/animal based on market conditions at the time. Unfortunately, commercial growth performance estimates of sorted subpopulations are rare; accounting software programs generally produce a composite closeout representing the weighted average of these subpopulations. Closeout data from approximately eight million fed cattle (steers and heifers) over 3 years were used to assess relationships between cattle sex, feeding period length (initial BW or days fed), indicators of growth rate (ADG or DMI), external factors (year, calendar quarter, geography), and carcass outcomes. Carcass attribute frequency data (Prime, Choice, Select [QG], yield grade 4, yield grade 5 [YG]) were transformed as needed prior to stepwise regression procedures. Models explained the greatest amount of variation for carcass weight (R2 = 0.32 to 0.69), followed by QG (R2 = 0.11 to 0.27), and YG (R2 = 0.05 to 0.07). Examples are provided illustrating the impact of selected fatness endpoints on premiums and discounts.