Comparison of Breeding and Marketing Systems for Red Angus Cattle Using an Integrated Computer-Based Spreadsheet

Professional Animal Scientist, Oct 2004 by Miller, K E, Whittier, J C, Peel, R K, Enns, R M, Et al

A cost per pregnancy matrix was computed using the costs from the cost analysis section, conception rates, and estrous response rates if estrus detection is involved. The matrix also provided a clean-up bull cost that is to reach the final pregnancy rate goal. The costs for clean-up bulls were computed using the percent pregnant to AI, bull-to-cow ratio, expected years of service, total bull costs, total cows being bred, and expected final pregnancy rate. The bull-to-cow ratio is projected through the costs on the portion of cattle that do not conceive via AI. This provides the opportunity for the beef cattle manager to decrease the number of required bulls. The total costs in the matrix reflect the sum of the AI and clean-up bull costs to achieve the projected final pregnancy rate.

Genetic Evaluation. The spreadsheet was developed with data from 581 Red Angus-sired calves from a cooperating ranch located at Briggsdale, Colorado. These animals were individually identified from conception to harvest at a common backfat endpoint. Calves were sired by AI or in single sire mating pastures. Means and standard deviations (Table 2) were calculated for the following: weaning weight, age, yearling weight, carcass weight, backfat thickness, longissimus area, and USDA yield and quality grades.

Animal information was sorted by computed expected progeny difference (EPD) accuracy by sire. Sires for the calves were placed into two groups, high and low accuracy, based upon the average accuracy for the group of sires used in a given year. Sires that were used over multiple years may have changed accuracy status as more information was accumulated from offspring. The base EPD data for the spreadsheet is given in Table 3. Sires placed in the low accuracy group were used as the natural service sire group, and sires in the high accuracy group were used as the AI sire group. A normal distribution was then created with the calf information to account for losses caused by mortality and retention of replacements to represent a population distribution. This provided information about the potential of the population without the loss of animals. The spreadsheet used these distributions to provide information regarding the genetic performance of the animals for weaning and carcass traits. Changes in genetics were added to performance information presently in the spreadsheet to assess whether the added genetic changes would influence revenue.

Marketing Options. Five different methods of marketing offspring (e.g., at weaning, finished cattle after retaining ownership, and three grid marketing options) were developed to calculate the greatest net return. Prices received over a 14-yr period, provided by Cattle Fax� (Centennial, CO) for 27-kg (500-pound) weaned calves were used to determine the price at weaning. Mean and distribution for each month were calculated and used to provide a mean price received, plus a confidence interval of two standard deviations below and above the mean. This confidence interval provided information to the user about expectations regarding the average revenue received. The spreadsheet was constructed to allow users to input the month of weaning and a price slide for that time period and the weight of the cattle sold at weaning. This provided an accurate account for the price received in relation to the time of year and weight of the calves. The price slide changed the price in relation to the weight of the cattle on a hundred weight basis. These computations were accomplished for both the natural service and AI-sired calves.