216 Assessment of Equations Relating Carcass with Empty Body Chemical Components in Growing/Finishing Cattle

Abstract

Abstract Existing equations to estimate empty body chemical composition from carcass chemical composition developed over 40 years ago using different cattle genetics. The objective of this analysis was to evaluate existing equations using cattle genetics from then to today. A literature search was performed to identify experiments measuring carcass and offal chemical composition by proximate analysis resulting in 88 treatment means from 11 experiments since 1982. Two sets of equations 1) Garrett and Hinman (1969; 10.2527/jas1969.2811) and 2) Ferrell et al. (1976; 10.2527/jas1976.4251158x) were used to compute empty body chemical components from carcass chemical components. Mean (SD) carcass fat and protein were 18.86 (8.37) and 18.18 (2.94) % of HCW, respectively, and empty body fat and protein were 18.25 (7.85) and 18.69 (2.32) % of EBW, respectively. Carcass chemical components were strongly correlated (≥ 0.98) with empty body chemical components. For Eq. 1, simultaneous testing of intercept equal to 0 and slope equal to 1 indicated that the intercept and slope for water, fat, ash, and energy were different than 0 and 1, but were not different for protein, whereas the intercept and slope were different for all components when using Eq. 2. Mean bias for chemical components ranged from -2.43 to 7.94% for Eq. 1, and -2.41 to 3.56% for Eq. 2. The mean bias was closer to 0 for water, fat and energy when using Eq. 2, but were closer to 0 for protein and ash when using Eq. 1. Offal chemical composition was a significant (P < 0.05) predictor of the difference between observed and predicted empty body components. Publication year was a significant (P < 0.05) predictor of the difference for protein and ash using either set of equations. In conclusion, both sets of equations were highly precise for all chemical components, and moderately to highly accurate, although later publication years had greater overprediction for protein.