A primary objective of this study was to determine whether the binary traits heifer pregnancy (HP) and subsequent rebreeding (SR) were heritable in an experimental population of Angus cattle. A second objective was to determine the nature of the additive genetic relationships among HP, SR, and stayability (S(5/1)) in the same population. Heifer pregnancy was defined as the observation of a heifer conceiving and remaining pregnant to palpation at 120 d, given exposure during the breeding season. Subsequent rebreeding was defined as the observation of a 2-yr-old conceiving and remaining pregnant to palpation at 105 d, given pregnancy as a yearling and exposure during the breeding season. Stayability was defined as the probability of a female having at least five calves, given she becomes a dam as a 2 yr old. Data were analyzed using a maximum a posteriori probit threshold model to predict breeding values on the liability scale and Method R procedures to estimate variance components in the determination of heritability (h2). Additive genetic groups were used in determining the additive genetic relationships among these fertility traits. Additive genetic groups were formed on one trait's breeding values and used in the prediction of another trait's breeding values. Analyses yielded h2 estimates that were out of the parameter space 8.5 and 46.3% for HP and SR, respectively, and 5.9% for the reestimation of S(5/1). The majority of point estimates outside the parameter space for SR converged toward 0, whereas those for HP and S(5/1) primarily converged toward 1. From the subsamples producing h2 estimates within the parameter space, average h2 for HP, SR, and S(5/1) were .21, .19, and .15, with standard deviations of .12, .14, and .08, respectively. The estimates of h2 indicate that HP and S(5/1) were heritable and should respond favorably to selection; however, SR did not appear heritable due to the large number of subsamples producing h2 estimates out of the parameter space. Fixed effect estimates for age of dam were significant for HP. From the analyses using additive genetic groups, the relationship among HP and S(5/1) appeared to be nonlinear. This potential nonlinear relationship seen between HP and S(5/1) indicates that selection for improved female fertility would be most effective by having predictions on both traits.
in its Own Fog? Over the past couple of decades, the beef cattle industry has become a confusing place to exist. Messages have been conveyed to producers at a fast and furious pace. This would not be a problem if these messages were consistent and if they were compatible with each other, yet this is far from the real situation. Daryl Tatum has been known to occasionally coin the term to describe confusion as "someone being lost in his/her own fog". Unfortunately, this verbage very accurately describes the beef cattle production environment of the 1990s. One could compose a lengthy list of dichotomies in the current beef cattle industry. A partial list might include: 1) A forage-based production system (low input) versus a concentrate-based feedlot system (high input). 2) Fierce pride in producer individuality and independence versus strategic alliances and cooperative relationships. 3) Segmentation and resulting inefficiencies versus vertical coordination and/or integration. 4) Traditional purebred cattle-focused seedstock production versus commercially-oriented specification seedstock production. 5) "Show cattle" versus "performance cattle". 6) Commodity-based marketing versus value-based marketing. 7) Totally "vested" beef cattle producers versus "less-vested" small landowners. 8) Public lands versus private land use for beef production. 9) "Artificially selected" cattle versus "naturally selected" cattle. 10) "Animal welfare" versus "animal rights ". 11) Systematic crossbreeding versus mongrelization. 12) Purebred breeding versus composite breeding. 13) Increased quality and consistency versus increased genetic variation. 14) High tech production versus low cost production. 15) Matching the cow to the production environment versus matching the calf to the marketing environment (i.e. cow adaptability versus carcass acceptability). The collective concerns and issues listed above, along with a number of others we could further list, have contributed to "the fog" for beef cattle producers. Given how spontaneously and explosively these issues can appear (or increase in importance), what is a cow-calf producer to do? The objectives of this presentation are to: 1) Provide an overview of how to match a Between Population Selection. Larry Cundiff and co-workers at the U.S. Meat Animal Research Center have conducted the most extensive genetic evaluation of breeds in the world over the past 30 years in the Germ Plasm Evaluation (GPE) program at the U.S. Meat Animal Research Center. The design for this project (Table 3) has allowed for the evaluation of a widely diverse set of breeds, as shown grouped by biological type in Table 4 (Cundiff and Gregory, 1999). From the collective results of this effort, they have reported that the magnitude of genetic variability between breeds is roughly equivalent to that within breeds (Table 5) for most performance traits. While this infers that genetic improvement is possible through proper breed selection implemented in designed crossbreeding programs (i.e. breed complementarity), it ...
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