Performance Testing at Angelo State University - 1998

[ Performance & Origin ] [ Performance & Origin II ] [ 1999 Performance Test ] [ Performance Testing 1998 ] [ Buck Performance Test ]

[ Home ] [ Boer History ] [ Business Planning ] [ Standards ] [ Meat Goat Market ] [ Meat Goat Performance ] [ Ethnic Calendar Related to Eating Goat Meat ]

This report was reported in the December 1998 issue of Goat Rancher and compiled by

• Dr. Dan Waldron, Texas A&M University, Texas Agriculture Experiment Station in San Angelo
• Dr. B. Frank Craddock Texas A&M University, Texas Agriculture Experiment Station in San Angelo

An 84-day meat goat performance test was completed on September 2, 1998 at Angelo State University in San Angelo, Texas. There were 261 bucks (Boer, Spanish and Crossbred) that completed the test.

The rationale for a central performance test is to try to accurately measure performance of animals from different ranches in a common environment so that performance is not influenced by different environments. If there are no pre-test environmental effect that influence performance, the observed differences in performance are better indicators of genetic differences that will be passed on to the next generation.

The test announcement requested that only bucks born between January 1 and March 31, 1998 be brought to test. The bucks were delivered to the ASU testing facility at San Angelo on June 1. The bucks were then allowed an adjustment period to get accustomed to the feed and facilities. The performance test started on Jun 10, All bucks were fed a growing/finishing ration in self feeders.

Ribeye area (REA) was measured from an ultrasound scan taken at the conclusion of the test.

Performance data is summarized by owner and sire groups. When a sire produces several sons with superior gain, a breeder can have more confidence that the observed superiority is genetic. Because some sires will have sons in more than one year, it will be possible to make comparisons of sires from the record from multiple years. As more performance data is accumulated, the accuracy of genetic evaluations increases.

Top 20, Ranked by Average Daily Gain