In the cow business there's a difference between genetic change and genetic improvement. Genetic change is as easy as tossing darts at an open page of a sire summary. Genetic improvement, most often achieved with careful aim at the combined production, management and economic aspects of a production environment, is a whole other story.
And, while for decades beef producers have found sire summaries to be of great value in learning genetic details of particular sires, limitations often surface when selecting for multiple traits. This is especially true when identifying sires a rancher hopes will have the most impact on profit in a business where a myriad of outside influences are constantly causing the target to shift.
“It's no secret most ranchers these days are interested in multiple-trait improvement,” explains Dorian Garrick, Colorado State University professor of animal science. “And, the bulls that are trait leaders for one trait are seldom the bulls of most interest from a multi-trait perspective.”
So, it makes sense to take aim at sires with traits that will interact to increase overall ranching profits — rather than using sires that simply lead to genetic change.
Beyond EPDs and indexes
Enter the new age of genetic selection tools — the World Wide Web and an associated decision support tool.
At last July's Beef Improvement Federation meeting in Billings, MT, Garrick unveiled a new, interactive Web-based tool that leaps over sire summaries, index selection and even filtering programs linked to online sire summaries.
Developed by the National Beef Cattle Evaluation Consortium (NBCEC), the “Surfing for Genetics” database (see sidebar on page 26) was launched for beef producers to use in customized sire selection with expected progeny differences (EPDs) and multi-breed evaluations.
“This Web-based decision support tool provides justification as to why particular animals get the values they get,” Garrick says. “It supports your decision by providing you with relevant information as to the ramifications of your selection.”
Rather than assessing overall merit by multiplying EPDs and economic values, the decision support tool predicts phenotypic performance and constructs a financial budget using those predictions. The overall merit is the bottom-line budget; but the user can inspect the budget in its entirety.
Garrick points out one of the early tools for quantifying the relative impact of alternative sires — EPDs — are very helpful for single-trait selection. But, real-life selection on multiple traits requires tools that jointly and simultaneously consider a portfolio of EPDs.
As traditionally developed, selection indexes multiply each EPD by an economic value to assist in multi-trait selection, but they have some limitations, Garrick explains.
First, the selection index may not be based on the specific production, management and economic circumstances relevant to your herd. Further, the assumed circumstances aren't always clear to anyone other than the index's inventor.
Second, index values essentially make most of the decisions for you, with little ability to provide explanation as to why one bull is predicted to outperform the other.
“There are a number of reasons why EPDs aren't sufficient information to make good decisions without further analysis,” Garrick says. These reasons have their basis, respectively, in statistics, genetics, systems biology, nutrition, economics and probability.
Let it do the math
The Web is an ideally suited tool to crunch the numbers needed to analyze the entire portfolio of EPDs for a subset of interesting sires along with the other genetic, management and economic variables found on a ranch — something ranchers might have traditionally expected from an EPD. Garrick lists six ways the new interactive selection tool will enhance selection beyond solely looking at EPDs in an electronic database:
Interpretation of threshold traits: Calving ease, stayability and heifer pregnancy EPDs, for example, are based on categorical observations. The impact of altering merit for any one of these traits depends on your current level of performance.
The difference in the number of difficult calvings that would be observed between an average- and an easy-calving bull will vary from one ranch to another. This isn't reflected in published EPDs but is calculated in the decision-support tool.
Interactions between economically relevant traits: The weaning-weight EPD indicates the EPD in weaning weight — if the offspring of alternative sires were the same sex and born on the same day, to cows of the same age. However, changes to herd stayability alter the proportions of young and old cows, changing the average weaning weights observed and for which a rancher would get paid. The saleable weaning weight also varies with heifer pregnancy EPDs and calving ease EPDs among other factors.
Assessment of nutritional implications: More productive animals are typically more efficient, but they normally require more feed each day than average-productivity animals. In a cow-calf system, additional feed must be purchased or fewer cows run on the same range. Assessing the change in feed intake that accompanies alterations to growth rate, mature size, herd age structure and offspring growth rate can be done with nutritional tables, but the arithmetic is tedious if it needs to be repeated many times.
Assessment of financial implications: Few ranchers enjoy doing budgets. It's straightforward to multiply sale items, such as weaning weight, by expected prices. For most, accounting for cost items such as veterinary bills for calving assistance by the relevant expenses isn't difficult. But, it's more appealing when the computer can do all these calculations automatically using productivity differences obtained from EPDs along with a rancher's own price and cost expectations.
Accounting for bulls with less-than-perfect accuracy: Bulls with accuracy values less than 1 may be better or worse than your expectations based on their published EPDs. The published accuracy can be used to quantify the likely change in EPDs that would result when more information becomes available on the progeny of a bull.
We seldom complain if a bull turns out better than expected, but there's an equal chance he may turn out worse. The risk associated with using younger bulls can be quantified to minimize the chance you might choose a bull that reduces your profitability.
Multi-breed evaluation and crossbreeding: Mating bulls and cows of different or mixed breeds results in changes in performance as a result of heterosis. Calculating the contribution of heterosis to animal performance requires knowledge of heterosis factors between the pairs of breeds involved and for each of the traits of interest. Web-based decision support software can access such figures and undertake the relevant calculations to predict phenotypic performance. The industry has shown enormous interest in converting the current evaluation system that produces purebred EPDs into a multi-breed system.
A million good bulls
Garrick says the Web-based decision support tool will allow ranchers to define a herd's parameters, then observe interactions between different economically relevant traits.
“For instance, the tool will mate a producer's herd to the sire he or she selects and create a daughter herd to compare to your current herd in terms of production, incomes, costs and profit,” he says.
The prototype “Surfing for Genetics” Web site currently allows producers to sort between Red Angus artificial insemination (AI) sires. A new release will soon make AI sires and yearling bulls available in a database — including one million bulls from about eight breeds.
Garrick says a “feedlot module” of the selection tool is being developed to complement the basic cow-calf module.
“It's a natural step forward to consider all the parameters of taking a calf from weaning and into the feedlot,” he says. “We believe better decision support will give better decisions for profit.”
Give it a try
The National Beef Cattle Evaluation Consortium (NBCEC) developed a Web-based decision support tool to help ranchers determine the effects of mating various bulls to their cow herds. In a step-by-step format, the Web site uses a series of queries and input forms in making sire selection decisions based on expected progeny differences (EPDs) and multi-breed evaluations.
It begins with inputs for various herd parameters under the categories of production, management, genetics and economics, from which it calculates a ranch's “Status Quo Base Herd Output.” Next, the program provides an interactive “Sire Selector” that allows the user to develop a short list of possible sires identified by name, breed and registration number that can be examined for their EPDs and EPDs accuracy.
“We're allowing you the power to play with the models yourself,” says Dorian Garrick, Colorado State University professor of animal science. “It will tell you the ramifications to your herd and show you predicted income and expense from that bull.”
Find it at: http://ert.agsci.colostate.edu.