Abstract
Abstract Multivariate statistical analysis of reverse phase-high-performance liquid chromatography (RP-HPLC) chromatograms of ethanol (70%)-soluble and -insoluble fractions and free amino acids from miniature Cheddar-type model cheeses was performed to evaluate effects of different single-strain starters on proteolysis. The statistical analysis was done by using principal component analysis (PCA) and hierarchical cluster analysis (HCA). Based on results from the statistical analysis, we were able to group strains according to their effects on chromatographic profiles and free amino acids. PCA, using variables standardised to zero mean, and the covariance matrix made it possible to identify peaks which were strongly influenced by the different starters. Multivariate statistical analysis of chromatographic profiles was a more objective and powerful approach for evaluating proteolysis in cheese, than visual assessment of the chromatograms.
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