Principal Component Analysis as an exploration tool for kinetic modeling of food quality: A case study of a dried apple cluster snack Original Research Article

A Multivariate Accelerated shelf-life Testing (MALST) study of a dried apple cereal-like snack (commercially known as cluster) stored at 18 °C, 25 °C or 35 °C for 17.5 months was conducted. The measured attributes were water activity (Aw), color DE, moisture and sensory properties (aroma, taste, texture and color). The data were deployed to adjust the multivariate kinetics (including the interactions of the attributes) using Principal Component Analysis (PCA), and the results were compared to those obtained using a univariate kinetic model. The predicted shelf-life for the reference storage condition obtained using the multivariate model was 18.3 months, whereas a predicted shelf-life of 15.6 months was obtained using the univariate model. Thus, although the results of both methods are similar, the multivariate kinetic model revealed all of the product shelf-life attributes and their interactions. Finally, the multivariate model reflected the variability of the biochemical phenomena underlying product degradation.