Application of electronic nose and GC-MS for detection of strawberries with vibrational damage

Abstract

Objectives: This study evaluated the potential of using electronic nose (e-nose) technology to non-destructively detect strawberry fruits with vibrational damage based on their volatile substances (VOCs). Materials and methods: Four groups of strawberries with different durations of vibrations (0, 0.5, 1, and 2 h) were prepared, and their e-nose signals were collected at 0, 1, 2, and 3 days after vibration treatment. Results: The results showed that when the samples from all four sampling days during storage were used for modelling, both the levels of vibrational damage and the day after the damage happened were accurately predicted. The best models had residual prediction deviation values of 2.984 and 5.478. The discrimination models for damaged strawberries also obtained good classification results, with an average correct answer rate of calibration and prediction of 99.24%. When the samples from each sampling day or vibration time were used for modelling, better results were obtained, but these models were not suitable for an actual situation. The gas chromatography-mass spectrophotometry results showed that the VOCs of the strawberries varied after experiencing vibrations, which was the basis for e-nose detection. Limitations: The changes in VOCs released by other forces should be studied in the future. Conclusions: The above results showed the potential use of e-nose technology to detect strawberries that have suffered vibrational damage.