Categorization of Beef Longissimus Lumborum and Gluteus Medius Muscles Based on Metabolic Attributes Is More Informative Than Muscle pH

Muscle metabolism is generally monitored using muscle pH. However, pH does not account for all metabolic effects on meat quality. We evaluated the effectiveness of agglomerative hierarchical clustering in creating clusters of beef longissimus and gluteus medius muscles based on metabolic traits. Beef carcasses (n = 100) were selected at grading based on longissimus thoracis pH (< 5.6, 5.60 to 5.74, 5.75 to 5.9, and > 5.9). Metabolic traits characterizing oxidative and glycolytic metabolism were measured on each muscle. A subset of longissimus lumborum muscles were placed in an in vitro glycolytic system with 2 temperature decline rates to evaluate glycolytic efficiency. Gluteus medius muscles exhibited more oxidative metabolism than longissimus lumborum muscles. Metabolic traits measured in one muscle were generally positively correlated to the same trait measured in the other muscle. Clustering of metabolic traits within each muscle produced similar dendrograms. Clustering of longissimus lumborum muscles based on metabolic traits produced 4 distinct clusters (High pH, Glycolytic, Chaperone, and Soluble). Clustering of the high pH was generally, but not totally, in agreement with classifications based on pH. The remaining longissimus lumborum clusters did not differ in pH. Similar to the longissimus lumborum clusters, the gluteus medius clusters included High pH and Glycolytic clusters and a cluster with low values for protein solubility and peroxiredoxin 2 abundance. In the in vitro system, pH decline was affected by a cluster × temperature decline rate interaction (P < 0.05). The soluble cluster had the least extensive pH decline under the fast temperature decline but had the most rapid pH decline at the slower pH decline. These results indicate that clustering muscles based on several metabolic factors was more effective than categorizing muscles based on muscle pH. Metabolic variation identified by clustering was related to differences in the glycolytic machinery that can be differentially impacted by chilling rate.