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.

Repeated-measure animal models to estimate genetic components of mature weight, hip height, and body condition score.

Information on mature weight, hip height, and body condition score from Angus cows was analyzed to estimate variance components and compare prediction models. Observations from repeated measures were analyzed with animal models with or without condition score as a covariate and with or without an effect for permanent environment. Heritability (repeatability) estimates for mature weight, hip height, and condition score from Method R procedures were 0.

Additive genetic relationships between heifer pregnancy and scrotal circumference in Hereford cattle.

The objective of this study was to determine an appropriate method for using yearling scrotal circumference observations and heifer pregnancy observations to produce EPD for heifer pregnancy. We determined the additive genetic effects of and relationship between scrotal circumference and heifer pregnancy for a herd of Hereford cattle in Solano, New Mexico. The binary trait of heifer pregnancy was defined as the probability of a heifer conceiving and remaining pregnant to 120 d, given that she was exposed at breeding.

Shortcomings of current genetic evaluation systems.

Genetic evaluation, as the term is used today in the beef cattle and sheep industries, refers to the calculation and dissemination of genetic predictions for individual traits. If genetic predictions are to be used wisely, however, genetic evaluation should be broadened to include multiple-trait selection technology, preferably technology that is customized for individual commercial and seedstock producers. Most of the recent research in the area of genetic prediction/multiple-trait selection has focused on the use of economic selection indexes that incorporate genetic predictions produced within breeds.