AI-Assisted Optimization of Chitosan-Based Modified Atmosphere Packaging (MAP) to Enhance the Shelf Life of Banana Fruit

Abstract

Banana is one of the most important tropical fruits consumed worldwide due to its nutritional value, pleasant taste, and economic significance. However, bananas are highly perishable and undergo rapid ripening after harvest, resulting in significant post-harvest losses during storage, transportation, and marketing. Traditional preservation methods often fail to maintain fruit quality for extended periods while ensuring environmental sustainability. Modified Atmosphere Packaging (MAP) has emerged as an effective technology for controlling the gaseous environment surrounding fruits, thereby reducing respiration rate and delaying senescence. In recent years, chitosan-based coatings have gained considerable attention because of their biodegradable nature, antimicrobial properties, and ability to form protective films around fresh produce. This study explores the integration of Artificial Intelligence (AI) with chitosan-based MAP systems to optimize storage conditions and improve the shelf life of banana fruit. AI techniques are utilized to analyze complex interactions among temperature, humidity, gas composition, and coating concentration, enabling accurate prediction of fruit quality parameters during storage. The optimized packaging system significantly reduces moisture loss, microbial growth, and physiological degradation while maintaining texture, color, and nutritional quality. The results demonstrate that AI-assisted optimization can enhance the efficiency of chitosan-based MAP by identifying ideal storage conditions that maximize preservation performance. Furthermore, the use of biodegradable packaging materials contributes to environmental sustainability by reducing reliance on synthetic plastics. The integration of intelligent algorithms with sustainable packaging technologies offers a promising approach for minimizing post-harvest losses, improving food security, and increasing profitability within agricultural supply chains.