Project Summary

Augmentation of Near Infrared (NIR) and in-plant Beef Video Image Analysis (VIA) Systems to Sort Carcasses into Tenderness Categories

Principle Investigator(s):
Brad Morgan
Oklahoma State University
Completion Date:
May 2008



As part of its effort to implement value-based marketing, the beef industry began investigating the use of instruments to improve characterization, sorting and pricing of cattle and beef carcasses nearly three decades ago. Work continues to enhance video image analysis systems, so that they can more accurately sort carcasses for various attributes. Accurate tenderness prediction could be one of the most valuable aspects of video image analysis and would create more value-based marketing opportunities for producers. 

The objectives of this study were:  

  1. To validate the effectiveness of augmenting an in-plant, video image analysis (VIA) system with a near-infrared (NIR) system to obtain an accurate 14-day tenderness prediction; 
  2. To determine the combined effect of near-infrared and video image analysis on the effectiveness of predicting seven-day and 14-day tenderness from four subprimals in various quality grades, observe if a relationship exists between predicted longissimus shear force and tenderness of short-term muscles, and obtain consumer perceptions of longissimus steaks that were categorized as “tender,” “intermediate,” or tough.

To view the complete Project Summary, click the Download button above.