Genetic Prediction of Efficiency in the Future:
An American Perspective 

The industry has picked all the low-lying fruit in terms of genetic evaluation, John Pollak, Cornell University, told attendees of the 34th annual Beef Improvement Federation (BIF) meeting in Omaha, Neb. It’s going to take some effort to stretch to the next level, he said.

“We have done a very good job historically in data collection, genetic evaluation and selection for weight,” Pollak said, adding that the industry has had moderate success in analyzing traits such as calving ease and carcass quality. However, establishing genetic predictors for traits such as reproductive performance and efficiency is much harder.

The problem today is not in finding the genetic evaluation systems to analyze this type of information, but in developing adequate means of data collection and processing, Pollak said. Whole-herd reporting is a sign of progress, allowing producers to look at heifer pregnancy and cow longevity. Ultrasound is improving the ability to collect large amounts of data on carcass characteristics.

“We are having to think more and more — if we’re going to start reaching higher on that fruit tree — about what kinds of programs need to be in place to get that data,” Pollak said.

Pollak said he believed the future of genetic prediction of efficiency would necessitate using biological modeling, such as that used in the Cornell Value Discovery System (CVDS) Danny Fox had described in an earlier presentation. 

Pollack also described a project being at the Bell Ranch in New Mexico. The objective of that project is to set up a protocol for collecting data and progeny testing in commercial herds, including herds with multiple-sire breeding pastures, with the goal of generating expected progeny differences (EPDs) on commercial bulls. One of the EPDs the study is hoping to look at is feedlot efficiency using predicted phenotypes. For more information about the project, visit www.Thebellranch.com.
— by Shauna Rose Hermel