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In beef, tenderness is considered the most important, yet the most variable, of all palatability characteristics.  Despite the current USDA grading system and branded beef programs implemented by the beef industry, there continues to be difficulty in accurately identifying and segregating carcasses into tenderness categories.  The industry has identified the development of an accurate method to predict tenderness as a high priority.

 

The purpose of this study was to employ quantitative electrophoretic image analysis of bovine longissimus dorsi to segregate beef carcasses into tenderness categories at the time of grading in the processing plant.

 

Two 2.5 cm steaks were removed from the loin area from 20 carcasses at the time of USDA grading, approximately 36 hr postmortem.  One steak was aged and subjected to Warner-Bratzler shear force (WBS) analysis.  The other steak was frozen, myofibrils extracted, subjected to SDS-PAGE and the gel fluorescently stained.  Gel images were captured, digitized, normalized, bands quantitated and subjected to analysis by a reverse stepwise linear regression.

 

This method was able to correlate postmortem myofibrillar fingerprints and ultimate WBS analysis with an r²=0.82.  In all, the intensities of seven bands were identified as being either a positive or negative parameter in a linear equation predicting ultimate WBS values.

 

These findings lay the foundation of future strategies for developing consistently reliable and accurate methods of predicting meat tenderness based on the understanding of the fundamental cellular mechanisms underlying the proteolytic breakdown of muscle proteins during the aging process.  For instance, the peptides identified by this method can be removed from the gel, and employed as immunogens or submitted for amino acid sequencing.  This information could be used to not only develop an immunological method for determining tenderness but also establish a clearer understanding of the mechanisms of postmortem development of tenderness.