DOI: 10.1111/jfpe.70845 ISSN: 0145-8876
A Novel Sustainable
Morus alba
Edible Coating Integrated With Hybrid Deep Learning Based Optimization Algorithm for Tomato Shelf‐Life Enhancement
A. S. Vijay Vikram, K. Geetha, C. Samuvel, G. Sireesha ABSTRACT
Tomatoes are very perishable climacteric fruits that require a considerable amount of moisture, soften, and get spoiled by microbes after harvest, causing loss of quality and food. Thus, a sustainable approach is needed to preserve the nutritional quality and microbial safety of the products over a longer period. This study aimed to assess the application of
Morus alba
leaf extract (MLE) rich in bioactive and antimicrobial compounds as a nanoparticle‐reinforced Edible Coating (EC) with chitosan and cellulose to enhance tomato postharvest preservation. Roma tomatoes were coated with six formulations and stored under controlled conditions for 25 days. The physicochemical and nutritional properties and the microbiological properties were systematically evaluated, and a hybrid Deep Reinforcement Learning–Shark Smell Optimization (DRL‐SSO) model was used to predict the coating performance. The optimized formulation significantly delayed weight loss (6.0% ± 0.4%) compared with uncoated tomatoes (21.9% ± 1.2%) while also retaining higher firmness (9.50 ± 0.32 N vs. 6.51 ± 0.28 N). Optimized coating also resulted in lower black spots (4.5% ± 0.3%) and higher total soluble solids (12.0% ± 0.6%), as well as higher contents of flavonoids (28.0 ± 1.4 mg/g) and ascorbic acid (28.5 ± 1.1 mg/g). Microbial growth was also significantly reduced, and prediction errors of the model DRL‐SSO ranged from 0.03% to 0.055% for the various quality attributes. The experimental outcomes show that nanoparticles coated with edible mulberry from
Morus alba
are an efficient and sustainable means to extend shelf life, enhance quality, and facilitate postharvest management of tomatoes.