Monitoring strawberry (Fragaria × ananassa) quality changes during storage using UV-excited fluorescence imaging

The strawberry (Fragaria × ananassa Duch.) is a popular fruit worldwide due to its attractive smell and good taste. However, a strawberry has a short postharvest life because of its fast deterioration, including softening. Until now, most sensing methods, like multispectral imaging and the electro nose sensor, were expensive. On the other hand, a non-destructive UV-induced fluorescence imaging method has the potential advantage of being low cost and detecting fruit quality changes in real-time. This research aims to establish a monitoring model for strawberry quality, especially firmness, using a machine vision system with UV LEDs for exciting fluorescence in the visible region. Strawberries were stored at 10 °C for 11 days in the experiment. Standard quality characteristics, firmness, and acidity, as well as fluorescence images and excitation-emission matrix (EEM) were captured during the experiment. Results showed that firmness decreased as storage time increased. The peak fluorescence intensity at wavelengths potentially be associated with amino acids and p-coumaric acid also increased during storage. The results of our analysis reveal a noteworthy correlation between the fluorescent component observed in Peak B of EEM measurements and firmness of strawberries during storage, as evidenced by a correlation coefficient of 0.89. These findings suggest that the aforementioned association may serve as a reliable index to estimate strawberry quality (firmness) over time. Furthermore, p-coumaric acid has a blue fluorescence in visible range when excited with 365 nm UV light. Thus, a machine vision system incorporating a cheap 365 nm UV LED light source and RGB camera could be developed to monitor strawberry quality decay during storage. To explore this possibility, the multiple color space from UV images of 77 strawberries were used to develop a estimation model for estimating the firmness of strawberry. The Partial Least-Squares Regression (PLSR) model showed the coefficient of determination R2 in calibration, prediction and cross-validation were 0.82, 0.79 and 0.83, and corresponding Root Mean Square Error (RMSE) values were all 0.04. This study demonstrates that a low cost, real-time UV fluorescence imaging-based sensor system could be used to estimate strawberries' firmness during storage.