Establishing relationships among specific quality traits is important if significant progress toward developing improved pork quality is to be realized. As part of a study to examine the individual effects of genes on meat quality traits in pigs, a three-generation resource family was developed. Two Berkshire sires and nine Yorkshire dams were used to produce nine F1 litters. Sixty-five matings were made from the F1 litters to produce four sets of F2 offspring, for a total of 525 F2 animals used in the study. These F2 animals were slaughtered at a commercial facility upon reaching approximately 110 kg. Carcass composition traits, pH measurements, and subjective quality scores were made at 24 h postmortem. Loin samples (n = 525) were collected at 48 h postmortem, and meat quality traits were evaluated. These traits included pH (48 h), Hunter L-values, drip loss, glycolytic potential, ratio of type IIa/IIb myosin heavy chains (IIa/IIb), total lipid, instrumental measures of tenderness using the Star Probe attachment of the Instron, cook loss measurements, and sensory evaluations. Significant phenotypic correlations were found between many carcass, instrumental, and biochemical measurements, and sensory quality traits. Star Probe measurements were significantly correlated with drip loss (0.29), glycolytic potential (0.30), pH (-0.29), total lipid (-0.14), and Hunter L-values (0.28). Drip loss was significantly correlated with glycolytic potential (0.36), pH (-0.28), IIa/IIb (-0.10), and Hunter L-values (0.33). Hunter L-values were also significantly correlated with total lipid (0.33) and IIa/ IIb (-0.11). Sensory tenderness, flavor, and off-flavor scores were significantly correlated with drip loss, pH, and glycolytic potential measurements. Marbling score, total lipid, and drip loss were not significantly correlated with sensory juiciness scores, but cooking loss was. Marbling and total lipid were significantly correlated with firmness scores (0.37 and 0.31, respectively). Taken together, the data in this study suggest that changes in some meat quality traits can affect many other meat quality attributes. The correlations yield information that could aid in directing future studies aimed at understanding the underlying biological mechanisms behind the development of many quality traits.