crucial for food quality assurance. Near-infrared (NIR) spectroscopy has become remarkably valuable in the agri-food sector. The aim of this study was to test NIR coupled with multivariate data analysis as a non-destructive tool to monitor apple quality during short-term storage. Methods: NIR was used to test apples (n=171) from four varieties and with varying levels of freshness. Each sample was measured immediately after harvest (at time T0) and after 14 days of storage at 10 ˚C (T14) in a non-destructive manner. Pattern recognition techniques including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to classify the apples. Variable importance in projection (VIP) was used to identify NIR spectra ranges that contributed significantly to the discrimination between fresh and stored apples. Results: The classification model distinguishing apples according to variety was characterized by high classification performance reflected in a misclassification error below 1%. The model for apple freshness discrimination also showed good classification performance with errors at the level of 7.9% and 5.8% for validation and prediction, respectively. The global model of eight classes including both apple variety and freshness was characterized by misclassification errors in the range of 1.2–6.3% for validation and 2.0–3.9% for prediction. The VIP method revealed that the spectral ranges contributing significantly to the freshness classification mainly corresponded to the absorption of water. Conclusions: NIR technology coupled with pattern recognition methods was found to be a promising tool for monitoring the overall loss of quality in fresh apples during short-term storage. The results may contribute to the development of a system supporting apple quality control and logistics during storage, e.g., while awaiting sale, transport or further processing. The findings are intended to guide various supply chain members and decision-makers so they can reduce post-harvest losses and improve the performance of the short fruit supply chain.