Evaluation of biological and economic efficiency of the All Heifer, No Cow beef production system using a system dynamics model based on 6 yr of demonstration herd data

Abstract

Alternative management strategies with no cows and all heifers may improve biological and economic efficiency of beef production. The All Heifer, No Cow (AHNC) beef production system involves insemination of nulliparous heifers with female sex-selected semen (FSS) to produce primarily female calves that are early weaned at 3 mo of age. Dams are finished on a high concentrate diet and harvested before 30 mo of age. The objectives of this research were to: 1) build a dynamic model of an AHNC beef production system to quantify system biological and economic efficiency; 2) compare effects of utilizing FSS vs. conventional semen on biological and economic efficiency; 3) evaluate what-if scenarios to determine the effects on biological and economic efficiency of changing variables ±5%, 10%, 15%, and 20% from initial observed values; and 4) evaluate the effects on biological and economic efficiency of changing variables ±10% from initial observed values. A model was built over a 21-yr horizon using Stella Architect. Biological parameter values in the model were based on the 6 yr of data collected from the management of an AHNC demonstration herd. In the model animal, total digestible nutrients (TDN) intake, hot carcass weight (HCW), and age at harvest were randomized. Feed, animal, and carcass prices included in the model were based on 10 yr of historical U.S. price data. Key response variables were biological and economic efficiency (mean ± SD). Biological efficiency was defined as the ratio of output (kilograms of HCW produced) to input (lifetime kilograms of feed TDN consumed), and economic efficiency was measured using a benefit–cost ratio (BCR) and unit variable cost (UVC). Over 40 simulation runs, the predicted mean biological efficiency was 0.0714 ± 0.0008. Economic efficiency was 0.95 ± 0.02 and US $445.41 ± 0.06 for BCR and UVC, respectively. Biological and economic efficiency was improved in the conventional semen scenario; biological efficiency was 0.0738 ± 0.0008, and BCR and UVC were 0.99 ± 0.04 and US $407.24 ± 0.006, respectively. Under this parameterization and market conditions, the AHNC beef production system failed to achieve profitability under any scenario that was evaluated. However, this review did not account for the potential increased genetic benefit from a decreased generation interval and the reduction in feed energy in comparison to a conventional cow/calf system.

Simulation Approaches Used for Management and Decision Making in the Beef Production Sector: A Systematic Review

“…The Northern Australia Beef System Analyser (NABSA) [ 27 ], for example, simulates the dynamic nature of beef enterprise to observe the change in herd structure over time. Many dynamic studies [ 66 , 67 , 68 , 69 ] simulate how the herd structure changes over time, leading to productivity and economic risks or benefits. Simulation of pasture conditions [ 70 , 71 , 72 ] is also another major focus of dynamic studies.…”

“…Most studies [ 24 , 26 , 40 , 97 ] that focus on increasing farm productivity include herd size and number of animals as an important indicator of productivity. Similarly, various studies [ 68 , 76 , 98 ] also make economic predictions based on herd structure. Therefore, the size and structure of the herd can be considered an important component in determining the productivity and economic returns of the farm.…”

Connectedness between Intensive and Extensive Ruminant Production Systems: Using Dairy Cow Feed Leftovers to Generate Out-of-Season Bio-Economic Indices in Goats

“…An actual consumer request is more efficient ruminant production of either milk or meat, requiring not only a reduction in the use of grain cereals but also efficient use of water, alongside a reduction in greenhouse gas emissions [50][51][52][53][54][55]. Most studies addressing ruminant production efficiency have used the output/input ratios but with an individual animal efficiency approach [20,56]; studies inferring a more integrative flock efficiency have been quite occasional [21,28].…”

A Sustainable Supply Chain Framework for Dairy Farming Operations: A System Dynamics Approach

“…By applying system dynamics, one can better understand how these various factors interact and how to adjust them to optimize performance. For example, system dynamics can be used to evaluate the economic efficiency of dairy cattle production systems [20]. Adjusting the feed ratio, grazing schedules, and reproduction planning can help identify the optimal efficiency for achieving maximum milk and meat production.…”