Economic Feasibility of Purchasing, Breeding and Marketing Bred Heifers and/or Pairs

Jon T. Biermacher, NDSU Extension Livestock Development Specialist; Tim Petry, NDSU Extension Livestock Marketing Specialist; and Gavin Eeg, Eeg Cattle Company | July/August 2026

The beef cattle herd contraction due to prolonged drought over the past four years has resulted in record-high cattle prices and raised questions about when ranchers will initiate expansion. In anticipation of an expansion, some producers have expressed interest in assessing the potential profitability of purchasing backgrounded (wintered) heifers, breeding them, and selling bred heifers or calving them out and selling pairs.

To address this question, we developed an Excel-based producer decision support tool that allows producers to enter their own estimates of prices and quantity parameters based on their farm’s historic records and local markets, and compare their projected sources of revenue, production costs and net returns ($/hd and $/operation) against NDSU’s projections. The decision tool was designed to easily allow producers to enter their own values for a set of price and quantity parameters and then view economic projections (revenues, costs, net returns) in a side-by-side comparison with NDSU projections. Once producers enter their parameters into the Producer Set Up sheet, they can easily use the tool to see how sensitive the economic results are to incremental changes to essential prices and quantity parameters.

To illustrate how the economic decision tool works, we created three alternative hypothetical producer scenarios to compare to a base-case NDSU heifer development scenario. Before we discuss the hypothetical producer setups, we first describe the base-case NDSU model for the heifer development enterprise.

The base-case NDSU model setup assumes an enterprise size of 100 purchased heifers initially weighing 750 pounds/head and projected to cost $3.60/lb in January 2026. We included our base-case projections for final market prices of $4,200/bred heifer and $4,300/pair and assume that producers would market bred heifers and pairs in January 2027. We assumed that producers choose to diversify the risk of putting all of their eggs in one basket and, therefore, only market 30% of their bred heifers (27 head) and let the remaining 70% (63 heifers) calve out and market them as pairs. We assumed a 10% industry-average number of open (nonpregnant) heifers that would be marketed as feeder heifers in April 2027.

We assumed heifers would graze unfertilized pasture for 180 days, each requiring eight acres of pasture at a rental rate of $30/acre. We assumed grain-based feed would cost $150/ton and average quality hay would cost $75/ton. We assumed that breeding bulls would cost $6,000/bull and would only be used for six months and then sold at a price 10% less than the initial purchase price. We assumed the distance from the sale barn to purchase and market heifers and pairs was 30 miles, and the transportation cost using a commercial truck/trailer was $3.75/mile. Lastly, we assumed that producers would use an artificial insemination (AI) breeding program with cleanup bulls (the model has been set up to allow producers to choose a natural breeding program as an alternative).

For our first scenario, we assumed our hypothetical producer would have the same projections for parameters as the NDSU base model, except (1) they would obtain more optimistic market prices, receiving $4,300 and 4,400 for bred heifers and pairs, respectively; (2) they would receive slightly better prices for feed ($130/ton) and hay ($60/ton); and (3) they would not use an AI program, electing instead to use a natural bull breeding program. The projected economic results for Scenario 1 are reported in Table 1. The results suggest that the hypothetical producer is projected to earn $90/heifer more in revenue, spend $49/heifer less in costs and earn a $139/heifer higher net return ($152 vs. $291/heifer) than the NDSU model. The extra revenue comes from better expected market prices and better feed and hay prices. Not using the AI program saves the producer $50/heifer in added costs compared to natural service.

For Scenario 2, we assumed our hypothetical producer uses the same parameters as the NDSU model in the first scenario, except that the hypothetical producer wishes to purchase and develop only 30 backgrounded heifers instead of 100. As a result, we parameterize both models to 30 head so our hypothetical producer can make a direct comparison. In addition, we assumed our hypothetical producer is willing to take on more risk and chooses to market only 10% of the group as bred heifers, preferring to market 90% as pairs because they have a better projected price. In contrast to Scenario 1, however, our hypothetical producer has to pay higher prices for feed and hay, costing them $175/ton for feed and $90/ton for hay, respectively. Lastly, our hypothetical producer prefers to utilize an AI synchronization program to breed their heifers. The projected economic results for this scenario indicate that our hypothetical producer would suffer a net return loss of -$81/heifer (-$2,436/operation) compared with the NDSU model’s projections (Table 1). The projected loss is due to the added costs ($98/heifer) associated with higher feed and hay, as well as the additional cost of an AI breeding program ($50/heifer in this scenario).

For Scenario 3, we assume that our hypothetical producer operates in Missouri and has a forage base that, when fertilized with 100 pounds per acre of actual nitrogen, can accommodate a stocking rate of four acres per heifer. Also, due to warmer climatic conditions, this producer’s pasture can support heifers for 270 days instead of the 180 that is typical in North Dakota. Our hypothetical producer also has access to rested breeding bulls that cost $6,000/bull and are replaced after four years of use. Further, because this would be a new enterprise for this operation, this producer wants to start by purchasing and developing 30 heifers. Because they are unsure about market prices, they will use the base-case market prices in the NDSU model. The results for this hypothetical producer scenario are also reported in Table 1. Overall, the projected results suggest that our hypothetical producer in Missouri would earn a net return of $287/heifer, which is $217/heifer more than our representative producer in North Dakota is projected to earn. The difference is due to lower winter feed costs, lower pasture costs from a higher stocking rate and reduced costs from using a natural breeding program.

Regardless of the individual producer scenario, we encourage producers to use the Producer Set Up sheet to conduct a simple sensitivity analysis to make sure economic projections hold up under small changes to the model’s assumed price and quantity parameters.

The decision support tool can be accessed at https://www.ndsu.edu/agriculture/ag-hub/heifer-development-decision-tool.

Send your questions to jon.biermacher@ndsu.edu.