Determination of Meat Quality Through Principal Components Analysis

Abstract

In the present investigation, Principal Component Analysis (PCA) was applied to various variables to describe meat quality. Sixteen meat quality variables were examined, and the analysis showed that 60.71% of the total variation was explained by the first three principal components. L*, a*, b* as colour data; odour, tenderness, flavour, acceptability as sensorial traits; hardness and chewiness as physical traits had the highest share in the total variation.