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Measuring What Matters

Highland Genetic & Performance Research

Pedigree, genomic, ultrasound, growth, and carcass information brought together to support informed Highland cattle breeding decisions.

Preserving Heritage. Measuring Performance.

Traditional Highland character and pedigrees remain central to our program. Modern performance tools add objective information that helps us evaluate animals, compare traits, and document progress over time.

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NWSS Highland Bull Performance Dashboard

The NWSS Highland Bull Performance Dashboard is a data-driven analytical tool that compiles and visualizes available National Western Stock Show Highland bull ultrasound measurements collected over more than 25 years. The dashboard allows users to explore historic performance trends and compare bulls using objective carcass measurements, including ribeye area (REA), ribeye-area ratio, intramuscular fat (%IMF), average daily gain (ADG), and backfat.

The purpose of the dashboard is to help breeders identify AHCA Highland bulls with carcass traits that align with their breeding objectives. By presenting historical performance data in an interactive format, the dashboard enables users to evaluate individual bulls, compare sires across multiple traits, and identify genetics that may contribute to improving carcass quality in future generations.

While the dashboard focuses on measurable performance traits, it is intended to complement—not replace—pedigree evaluation, phenotype, structural correctness, disposition, fertility, and the experienced judgment of cattle breeders.

Open the Dashboard
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How We Evaluate

Our approach combines multiple sources rather than relying on a single number.

  • Pedigree and breed character
  • Igenity genomic profiles
  • Ultrasound carcass measurements
  • Growth and estimated 205-day weight
  • Observed phenotype and disposition
Read Our Breeding Philosophy

Our Research Philosophy

The purpose of these tools is not to replace experienced cattle evaluation. They help document what we see, identify meaningful differences, and make selection decisions with a clearer understanding of the available evidence.