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This Article Full Text Full Text (PDF) All Versions of this Article: jas.2007-0095v1 86/2/413    most recent Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Price, D. M. Articles by Morgan, J. B. Search for Related Content PubMed PubMed Citation Articles by Price, D. M. Articles by Morgan, J. B.

Using the near-infrared system to sort various beef middle and end muscle cuts into tenderness categories

Oklahoma State University, Stillwater 74075

¹ Corresponding author: bmorgan{at}okstate.edu

The objectives of this study were to determine the effectiveness of a visible-near-infrared (VIS-NIR) system to predict the ultimate tenderness rating of various beef muscles and conclude if a relationship exists between predicted LM shear force and tenderness of other subprimal cuts. Carcasses (n = 768) were scanned with the VIS-NIR system in 2 commercial beef-processing facilities. Carcasses were categorized based on their predicted 14-d LM slice shear force value. After carcass scanning, 100 carcasses were randomly selected based on their tenderness classification, and subprimals (ribeye rolls, clods, knuckles, top sirloins, inside rounds, and eye of rounds) were removed, vacuum-packaged, and transported to the Oklahoma State University Food and Agricultural Products Research Center, where 2.54-cm steaks (n = 6) were fabricated and stored in refrigerated conditions (1°C ± 1) and aged for 14 d. The center steak from right-side subprimals was designated for slice shear force (LM) or Warner-Bratzler shear force (all other subprimals) analysis. The remaining steaks were categorized based on predicted tenderness taken at 2 d postmortem with the VIS-NIR spectrophotometer and used in a consumer taste study. The test population of carcasses (n = 100) scanned in-plant predicted 27 carcasses as tender, 45 carcasses as intermediate, and 28 carcasses as tough. The VIS-NIR system correctly classified 26 of the 28 (92.9% accuracy) tough carcasses. Overall consumer satisfaction was greatest (P < 0.05) for steaks classified as tender and was intermediate compared with the steaks classified as tough. It was concluded that in-plant VIS-NIR scanning can properly identify and sort carcasses into tenderness groups, which may lead to the development of certified not-tough programs.

Key Words: beef • near-infrared • quality grade • tenderness