The Use of principal component analysis (PCA) for evaluating results from pig meat quality measurements

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The relationships between different meat quality methods, i.e. pH, meat colour, protein extractability and pigment content, measured on Swedish pig carcasses, were analysed by principal component analysis (PCA). The result indicated that when using PCA for selection among the meat quality methods used, the ultimate internal reflectance explained the greatest proportion of the total variance. The results of this study show that PCA is a simple method of finding objects with different characteristics (e.g. outliers and various quality classes) and for variable selection.