Multivariate Examination of Metabolic Contributions to Beef Longissimus Lumborum Flavor

We examined the impact of muscle metabolic capacity on beef longissimus lumborum flavor. Beef carcasses were selected to have normal or dark cutting lean color (n=160, each) and aged until 13 d postmortem. Muscle pH, glycolytic potential, mitochondrial DNA copy number, instrumental lean color, myoglobin concentration, carbonyls on sarcoplasmic proteins, initial metmyoglobin formation, bloom, proximate composition, slice shear force, sarcomere length, desmin degradation, overall tenderness, juiciness, and flavor profile were determined. Carcasses were clustered based on metabolic characteristics into dark cutting classes (Control, Shady, Moderate, and Severe), which were compared using analysis of variance and multiple factor analysis. Clusters were in general, but not complete, agreement with classifications based on muscle pH. Multiple factor analysis produced 2 dimensions that explained 30.8% and 13.8% of the variation, respectively. Dimension 1 had strong negative loadings for muscle pH and strong positive loadings for glycolytic potential, L*, a*, b*, initial metmyoglobin formation, and bloom. Ratings for fat-like, overall sweet, sweet, and musty/earthy/humus had relatively weak positive loadings for dimension 1, whereas salt, sour, and metallic ratings had weak negative loadings for dimension 1. Overall tenderness and juiciness ratings, marbling score, intramuscular lipid content, carbonyls on sarcoplasmic proteins, and L* had positive loadings for dimension 2. Ratings for fat-like, beef flavor identity, and brown/roasted had positive loadings for dimension 2, and intramuscular moisture content, slice shear force, and mitochondrial copy number had negative loadings. Sample scores stratified dark cutting clusters along dimension 1, which agreed with univariate comparisons for these traits. Sample scores for dimension 2 were greater for Moderate and Control steaks than for Shady steaks. These data indicate that clustering was effective in segmenting them into groupings more indicative of the metabolic machinery than pH alone. Moreover, the semetabolic differences influenced animal variation in beef flavor profile.