ECONOMIC VALUES FOR BEEF PRODUCTION TRAITS IN ONTARIO

K.R. Koots, J.P. Gibson and C. Smith
Department of Animal and Poultry Science, University of Guelph

Summary

A bioeconomic model of an integrated beef production system was developed to derive economic weights. Fourteen genetic input traits were identified as potentially influencing returns and costs in the system. These were mature size, direct and maternal calving ease (in heifers and cows separately), cow fertility, calf survival, cow survival, peak milk yield, residual post-weaning growth rate, residual feed intake in growing animals, residual feed intake in mature animals, and residual slaughter weight and dressing percent at constant backfat thickness. Traits related to mature size were redefined as residual traits independent of mature size. A base situation is modelled which incorporates average returns and costs under typical production and marketing systems used in Ontario. Economic weights in the base situation suggest that all fourteen traits were of non-trivial economic importance. However, the relative importance of traits depended on the breed role.

Introduction

A critical step in any animal breeding program should be to define the breeding objective, yet it is often one of the last things to be considered or is not properly defined at all. Defining a breeding objective is especially challenging for improvement of beef cattle where genotypes and production systems vary considerably. Determination of an aggregate genotype requires a description of how genetic change affects profit. This involves evaluation of all sources of costs and returns in the production system. The numerous combinations of production systems and beef cattle genotypes can be simulated by computer modelling. The objective of this study was to develop a model of beef cattle production which can then be used to derive economic weights for traits important in an integrated enterprise.

A bioeconomic model of an integrated beef production system was developed. The model is deterministic and no genetic variation between animals within the herd is simulated. The following classes of animals are defined, feedlot steers and heifers (from birth to slaughter), replacement heifers, cows (age classes 2 to 10) and breeding bulls. The model is non-integerized (fractions of animals used) and the herd size is fixed. A one-year slice in time is modelled, but many beef production activities are simulated on a daily basis. Biological relationships among traits are taken from the literature. Where possible, data from the University of Guelph Elora Beef Research Centre are used to validate aspects of the model.

In the model, it is assumed that replacement heifers come from within the herd while breeding bulls are obtained from outside the herd. The 3 breed roles modelled were a purebreeding/synthetic mating system, a specialized dam line and a specialized sire line.

Profit per year is defined as net returns to labour and management for a constant herd size 50 breeding females. All returns and costs associated with the production of beef are accounted for. Revenues come from the sale of feedlot steers and heifers, and from cull replacement heifers, cows and bulls. Costs are incurred by feed (feedlot and cow-calf segments), labour and husbandry, bedding, marketing, veterinarian and medicine, and breeding (purchase of bull). Fourteen basic genetic traits are identified as potentially influencing returns and costs. Traits were chosen if 1/ they influence returns or costs in the integrated beef production system, and 2/ they could vary independently of other traits in the breeding objective. The traits are mature size, calving ease score (direct and maternal, both in heifers and cows separately), cow fertility, calf survival, cow survival, peak milk yield, residual post-weaning gain, residual feed intake in growing animals, residual feed intake in mature animals, residual slaughter weight at constant backfat thickness, and dressing percent at constant backfat thickness. A flow chart of the major feedbacks in the model is presented in Figure 1.

Base Model. Typical Ontario prices and costs are used in the base model. An important source of production costs information was the Ontario Farm Management Analysis Project reports. Annual average product prices and input costs were collected over a ten-year period (1981-1990) and were adjusted to 1990 dollars using appropriate price indices. Ten-years is chosen as an appropriate period over which to average costs and returns because this length of time covers the ten-year cycle in beef prices.

Husbandry costs included the costs of straw for bedding, veterinary costs, and miscellaneous and were charged annually on a per head basis on cows in the cow-calf segment, but on a daily charge per head in the feedlot segment. Marketing costs (check offs, commissions and shipping fees) vary considerably, based on the distance to packer, so average costs for Ontario producers are used, reflecting average transport distances.

Feed costs include the costs of pasture to meet the daily energy requirements of all livestock for half the year, and the costs of mixed rations (creep feed, cow winter ration and feedlot rations) used to meet the energy requirements of animals for the remainder of the year. The cost of milk consumed by nursing calves is determined from the daily energy requirements to support lactation of the dam.

Slaughter animals are individually marketed at optimum levels of backfat thickness (7mm; middle of A1 range in current Agriculture Canada grading system), so no prediction of carcass grade is required in the model. The price for slaughter animals is discounted for over- or under-sized carcasses in a step-wise fashion as is typical at Ontario packers. The average carcass price is estimated using a threshold model, where the proportion of carcasses in each price category is determined from normal distribution theory.

In the base model the culling policy is to maintain a constant herd size. So the number of replacement heifers required each year is determined from the number of dead or culled cows leaving the herd. Cows in each age class leave the herd because of 1/ failure to become pregnant; 2/ death or sickness; and 3/ age. Case 1/ is determined from probabilities of conception in heifers and in cows. Case 2/ is determined from cow survival (S3). A Markov chain is used to describe the culling process and of calculating the cow age distribution at equilibrium. Breeding is by natural mating, assuming a bull to cow ratio of 1 to 25. In the model bulls are purchased from outside the herd and are replaced every two years.

Economic values are derived by estimating the change in profit resulting from a small change in a given trait while holding all other traits constant. Each trait is altered an amount equivalent to 5 percent of the assumed phenotypic standard deviation. Threshold traits, CEDC, CECM, CEHD, CEHM, FR, S1, and S3, are changed .05 standard deviation upward on the underlying normal scale.

Economic weights for a purebreeding system as well as for separate sire and dam lines in a terminal crossbreeding system are presented in Table 1. The economic weights for a given trait depend on the different numbers of expression in the 2 mating systems modelled. In the terminal crossbreeding system, for example, economic weights for CECM, CEHM, FR, S3, PM and RFM would have a zero economic value in the sire line as these traits are only expressed in cows.

The traits considered here would form the aggregate genotype when constructing a selection index. Genetic correlations are, therefore, required between the 14 traits in the aggregate genotype and traits chosen for the index. Obtaining such parameters from the literature would be difficult, as many of the residual traits defined here have not previously been analyzed. Genetic correlations between the residual traits defined here and some easily recorded index traits, such as growth, would have to be estimated before selection indices could be constructed.

Alternatively, if genetic evaluations for traits in the aggregate genotype were available, these could be combined directly with economic values. Presently, genetic evaluations are not available for any of the traits in the aggregate genotype. Computing genetic evaluations for some residual traits, however, is possible under current recording programs as the component traits are often recorded. Residual feed intake in growing animals, for example, would be determined from measurements of growth, liveweight and dry matter feed intake. These traits are already being recorded in some bull test stations in Ontario. Other residual traits are similarly determined from component traits.

Conclusions

A bioeconomic model of integrated beef production is developed. The model is used to determine economic weights for 14 genetically independent traits. Their impact on profitability in integrated beef production enterprises under typical Ontario production and marketing circumstances suggest all traits examined have non-trivial economic weights and must be considered when developing selection indices.

Significance to the Industry

All traits modelled have non-trivial economic weights and so must be considered when developing selection indices. The next logical step would be to construct selection indices for various production circumstances. The ultimate goal remains the recommendation of appropriate selection indices to be used by the beef industry, which will incorporate genetic evaluations on relevant traits with the appropriate economic weights. Through examination

of the traits currently recorded and traits that could potentially be recorded, advice can be given to the beef industry on optimum recording strategies for genetic improvement. In this regard it is considered that, although economic weights were found to differ substantially between terminal sire and dam lines, the traits currently recorded by the industry may well not provide effective discrimination between the two selection goals.

Acknowledgements

This project was supported by the Ontario Ministry of Agriculture, Food and Rural Affairs.

Table 1. Estimated economic weights for genetic input traits for the base situation under a purebreeding/rotational mating system and for dam and sire lines in a terminal crossbreeding system.