Start Date: Jul 31, 2007
End Date: Jul 30, 2012
Major challenges of the beef cattle industry are to improve efficiency and reduce negative environmental impacts of animal production. Provision of nutrients (feed) constitutes about 65 to 75% of the cost of beef cattle production. Less than 20% of the nutrients consumed are converted to useful products. The incomplete and inefficient utilization of nutrients has an adverse effect on efficiency of production and a negative effect on the environment. Traditional approaches have resulted in successful alteration of production traits such as weight at slaughter, growth rate, mature weight, and body composition, but have not altered feed efficiency. Those approaches do not provide the ability to economically identify animals with high genetic merit for feed efficiency on a timely basis, because the required phenotypic data are impractical to obtain in normal genetic evaluation programs. Available evidence suggests feed consumption and related traits are likely to be moderately heritable. These traits are extremely important components in any strategy for the permanent, cumulative, and sustainable genetic improvement of biological and economic efficiencies of beef production. Application of quantitative trait loci (QTL) technology provides opportunities to improve feed efficiency in beef production. The identification of QTL would make it possible to utilize the relatively large amount of observed variation and moderate heritability in improving feed efficiency. However, currently there are no tools (EPD, QTL, or markers for QTL) that facilitate direct selection to modify feed consumption, feed efficiency, or nutrient requirements in the growing-finishing animal or productive female. Research in this project is being undertaken to study genetic and environmental factors that lead to variation in efficiency in beef production. This project addresses measures of efficiency at different phases of the production system to identify those factors that have additive merit and antagonistic relationships across the different phases of production. The initial component of the project is to develop facilities and methodologies to efficiently collect economically and biologically important phenotypic data relevant to efficiency. After developing capabilities to measure the phenotypes, the contribution of genetics and environment/management to variation in efficiency of production will be determined. Genetic variation will be evaluated using both quantitative genetics and QTL discovery. Information gained from both the genetic and environmental studies will be used to parameterize simulation models that provide decision support software to allow producers to simulate potential outcomes to optimize production efficiency when different combinations of animal genetics and management strategies are used.