Location: Forage and Livestock Production Research
Project Number: 3070-21610-003-001-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Sep 1, 2014
End Date: Sep 1, 2019
Objective:
1) To evaluate beef cattle genetics by determining the most nutrient-use-efficient ruminant genetic types in relation to reproductive efficiency, methane production by individual animals, and residual feed intake in the variable climate of the Southern Great Plains (SGP); 2) Use existing, and develop new, grazing datasets for implementation/integration into the Agricultural Policy Extender (APEX) model for evaluation of APEX's utility and robustness for modeling pasture systems of the sub-humid portions SGP and the more humid areas located in the southeastern United States.
Approach:
Investigators will address the various aspects of this research, including APEX modeling of animal grazing systems. The project will involve field, confinement feeding, and laboratory components that identify relationships of cattle genetics to calf production and cow reproductive efficiency, forage intake, methane production, and any interactions for identifying beef cattle with superior nutrient-use and reproductive efficiencies. Information will be used to help refine beef cattle production programs for better resilience to climate change. Additionally, the project will identify relevant historic and current datasets existing at the Texas A&M AgriLife Research and Extension Center, Overton, Texas (i.e., TAM-Overton), the ARS's Grazinglands Research Laboratory, El Reno, Oklahoma (i.e., ARS-GRL), and other relevant sites. Selected datasets will be collected and formatted for the APEX model and model simulations will be conducted and evaluated for pasture utilization and management and animal performance under diverse forage and animal grazing systems and climate scenarios. Also, new data (animal, plant, grazing, soil, and water) will be collected on the GRL model farm and unit source watersheds for refinement to APEX grazing routines. The APEX Information will be used to evaluate the effectiveness of conservation practices deployed in these pasture systems.
