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W R Shafer

Publications and source records attributed to W R Shafer.

2 recordsLinked to original sources

Genetic evaluation of beef carcass data using different endpoint adjustments.

Carcass data from 6,795 Simmental-sired animals born from 1992 to 2001 were used to determine whether adjustment to a constant age, back-fat, HCW, or marbling score would result in differences in heritability of the carcass traits and, correspondingly, if EPD calculated using those variance components and adjustments would result in sire reranking. The endpoints were age (EPA), backfat (EPF), HCW (EPC), or marbling (EPM). The traits analyzed were 12th-rib backfat (FAT), HCW, marbling (MRB), LM area (LMA), and percentage retail cuts (PRC). The data were analyzed using an animal model, where contemporary group was included as a fixed effect and was composed of slaughter date, sex, and herd. Random effects included in the model were direct genetic and residual. Estimates of heritability ranged from 0.12 to 0.14, 0.32 to 0.34, and 0.26 to 0.27 for FAT, HCW, and LMA, respectively, for the corresponding endpoints. Heritability for MRB was estimated to be 0.27 at all endpoints. For PRC, estimates of heritability were more variable, with estimates of 0.23 +/- 0.05, 0.32 +/- 0.05, 0.21 +/- 0.05, and 0.20 +/- 0.04 for EPA, EPF, EPC, and EPM, respectively. However, because the EPF and EPC adjustments adjust for a component trait of PRC (FAT and HCW, respectively), they may be altering the trait to one different from PRC. Spearman rank correlations between EPD within a trait using EPA compared with the other endpoints were >0.90 (P < 0.01) for FAT, HCW, MRB, and LMA. For PRC, Spearman rank correlations with EPA EPD were 0.73 (P < 0.01), 0.93 (P < 0.01), and 0.95 (P < 0.01) for EPF, EPC, and EPM, respectively. For most traits and endpoints, there was little reranking among sires when alternative endpoints were used. However, adjusting PRC to EPF appears to result in a greater heritability and substantial re-ranking of sires, potentially due to the adjustment changing the trait to one other than PRC.

Animals↗

Simulation of cow-calf production with and without realistic levels of variability.

The Colorado beef cattle production model, a whole-herd, individual-animal, life-cycle simulation model, was used to determine if level of simulated variability affects simulation results. Beyond variability created by deterministic equations describing known biological relationships and direct input, the Colorado beef cattle production model can produce additional variation in a number of traits through its capacity to generate multinormal deviates for each animal. Runs simulating cow-calf production under ample and sparse levels of nutrition were performed with less than realistic and realistic levels of variability for mature weight, milk production, gestation length, maintenance requirements, appetite, and combinations thereof. Under poor nutrition, simulation with less than realistic variability altered means for pregnancy rate, postpartum interval, milk production, weaning weight, and mature weight by up to 14%, 8.6 d, 0.8 kg/d, 9.6 kg, and 19.1 kg, respectively, in addition to changing the output for numerous other variables. The level of simulated variability affected the means of output variables through 2 mechanisms: (1) change in potentials due to differential culling, which can only take place if potentials are allowed to vary; and (2) further interaction with the model's nonlinear, deterministic equations. Our findings indicate that by not simulating realistic levels of variability, models with nonlinear functions may yield misleading results.

Analysis of Variance↗