Study of the variability of pork quality by principal component analysis (PCA)

Principal component analysis (PCA) was performed to study the relationships between technological, organoleptic, microbiological and zootechnie variables, measured on 264 pigs belonging to different Belgian production systems. The four first principal components explained 63 % of the total variability. The variables such as the pH, the electrical conductivity, the brightness and the color of meat presented the best correlation with the first principal component whereas the variables such as the E. coli Count and the Total Viable Count measured on the carcass, the hot carcass weight and the cooking loss of meat presented the best correlation with the second principal component. The first principal component was defined as an axis of technological and organoleptic quality whereas the second was defined as a microbiological axis. PCA allowed to differentiate two groups in terms of technological and organoleptic properties. A group including samples belonged to the first quality production chain and a part of samples belonged to the second was separated from the principal group by a lower pH, measured 45 minutes post mortem, and a paler meat