Multivariate relationships among pH, subcutaneous fat thickness, and color in bovine meat using canonical correlation analysis

Abstract

Background: pH, subcutaneous fat thickness (SFT), and color are fundamental variables to define the organoleptic characteristics of meat. However, multivariate relationships of those traits remain unexplored in bovine meat. Objective: To investigate the multivariate relationships among pH, subcutaneous fat thickness, and color parameters in bovine meat using canonical correlation analysis. Methods: A dataset containing 173 individual records of pH, SFT, and color parameters (a*: intensity of red color, b*: intensity of yellow color, and L*: lightness) from five Brazilian beef cut types (Breed: Nellore; cuts: acém, contrafilé, fraldinha, patinho and picanha) was constructed. Multivariate relationships between color variables (a*, b*, and L*) and chemical variables (pH and SFT) were explored using the CANCORR procedure of SAS. Results: Two canonical correlations between U (a*, b*, and L*; color variables) and V (pH and SFT; chemical variables) variates were significant (p<0.01). First and second canonical correlations were 0.463 and 0.282, respectively. Canonical weights for variates were for U1: a* = 0.707, b* = 0.406, and L* =-0.039; U2: a* = 0.364, b* =-0.898, and L* = 1.234; V1: pH =-0.376 and SFT = 0.935; V2: pH = 0.927 and STF = 0.356. Conclusion: Subcutaneous fat thickness significantly affected intensity of red and yellow colors, whereas pH significantly affected lightness. The results of this study may be useful for a better understanding of the role of muscle metabolism and its implications on the organoleptic characteristics of bovine meat.