The purpose of this study was to monitor changes in the quality of ginseng and
predict its shelf-life. As the storage period of ginseng increased, some quality
indicators, such as water-soluble pectin (WSP), CDTA-soluble pectin (CSP),
cellulose, weight loss, and microbial growth increased, while others
(Na2CO3-soluble pectin/NSP, hemicellulose, starch, and
firmness) decreased. Principal component analysis (PCA) was performed using the
quality attribute data and the principal component 1 (PC1) scores extracted from
the PCA results were applied to the multivariate analysis. The reaction rate at
different temperatures and the temperature dependence of the reaction rate were
determined using kinetic and Arrhenius models, respectively. Among the kinetic
models, zeroth-order models with cellulose and a PC1 score provided an adequate
fit for reaction rate estimation. Hence, the prediction model was constructed by
applying the cellulose and PC1 scores to the zeroth-order kinetic and Arrhenius
models. The prediction model with PC1 score showed higher R2 values
(0.877-0.919) than those of cellulose (0.797-0.863), indicating that
multivariate analysis using PC1 score is more accurate for the shelf-life
prediction of ginseng. The predicted shelf-life using the multivariate
accelerated shelf-life test at 5, 20, and 35°C was 40, 16, and 7 days,
respectively.