Impact of Single Step on Selection Indexes
by Lindsay King, assistant editor, Angus Journal
LOVELAND, Colo., June 21 — Implementing single-step methodology was a big task, but now the real job is showing the value in the headache of it all. Matt Spangler, associate professor of animal science at the University of Nebraska-Lincoln, discussed the far-reaching influence single step has and will have on selection indexes.
“In a nut shell, they (selection indexes) are a tool to enable informed multiple-trait selection. Every bull buyer does this in some manner already,” Spangler said. “This is a much more comprehensive and informed way to do it.
“Generally, the indexes we have now are static,” he continued. “As we customize these tools, it allows us to take advantage of the phenotypic enterprise means.”
The goal is to improve commercial profitability. The economic models used before are proving correct on average, but the single-step methodology takes what the producers value most into consideration when developing the index.
While relatively new to the beef industry (rolled out about 10 years ago), selection indexes have been used in other industries since 1942, Spangler said. “It is old hat to other industries — the idea of selecting candidates to be parents not just on selection indexes, but exclusively from those.”
Many things have an effect on selection indexes — the goal traits that a producer is looking for in a program is the main factor. However, expected progeny differences (EPDs) are always changing. As more data comes in and new EPDs are developed for a trait that is economically relevant, these selection indexes can be altered continuously.
“The selection indexes are fairly robust against genetic variance, but if we happen to use incorrect parameters, then those would need to be updated also,” Spangler explained. “Also, if the inference of a trait changes, then we have to re-evaluate the economic value we originally assigned to it.”
Other factors affecting the index include component trait accuracy, economic parameters and assumptions and assumed population means. Some make the mistake of blaming single step for inaccuracy or unwanted results after changing too many factors at once.
“The accuracy tells me when I make changes in the index how much I am improving the things that drive profitability, things in the goal,” Spangler said. “If I have more EPDs for economically relevant traits, that improves the accuracy of the index. When we include more economically relevant traits and increase the accuracy of the EPDs, we increase the accuracy of the index.”
Some traits may have a different scale and inference, examples being marbling and reproductive longevity. The definition for those traits may change, and so the means would need to be re-evaluated because their weight on the index would possibly increase or decrease.
“Sensitivity is determined by weight in the index,” Spangler said. “This single-step process increases accuracy of the selection index. We need to remember that re-ranking is not a bad thing if it moves us closer to the truth. Something we still need to figure out is when reasonableness checks are necessary.”
Some believe a universal index for use across all breeds should be the next step. However, Spangler explained how the variability of reasons for using a certain bull is significant enough to shoot down the idea of a universal index.
“Those phenotypic means of the given traits are inherently different and impact the economic values,” Spangler said. “We really need to think about that hard before we go down that path. Breeds are known for different things for a reason. That may not be quite as straightforward as wanting EPDs comparable across all breeds.”
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