Postharvest quality assessment of tomato during storage: An experimental and ML fusion

Abstract

In the present study, tomatoes' physical and chemical qualities were assessed experimentally while they were being stored after harvest for 24 days at ambient storage conditions (27 ± 2 °C). Every tomato quality attribute that was studied showed variations throughout storage. While the pH and sugar-acid ratio increased, firmness, ascorbic acid, acidity, and color change values decreased. The tomato's soluble solid content (SSC) increased and then reduced, ranging from 4.8 ± 0.05 to 4.4 ± 0.08 % Brix, while its pH and sugar-acid ratio fluctuated from 4.31 to 4.81 and 5.58–15.1 %, respectively. Moreover, overall quality index (OQI) models were formulated in terms of measured quality attributes and were validated with the sensory scores. The variations in the sensory overall quality scores were found to be consistent with the OQI predicted by Model M3. Moreover, the study's findings reveal that only 5 % of consumers preferred tomatoes when the quality index was assessed at 0.009. In contrast, 100 % of consumers rejected the tomatoes when the quality index was recorded at 0.004. Furthermore, 33 % of consumers expressed a favourable opinion towards tomatoes when the quality index reached 0.249. These results suggest that the optimal storage duration for tomatoes at ambient temperature is 12 days. Additionally, the overall quality index of the six distinct tomato cultivars was predicted using generalized machine learning (ML) models, which were shown to be successfully fitted (coefficient of determination, R² > 0.99) to the measured experimental data. These postharvest tomato quality prediction models could transform storage procedures by ensuring optimal conditions for increased shelf life and better-quality preservation.