Journal of Food Processing & Technology

Abstract

Revolutionizing Postharvest Management with AI-Powered Innovations

Kaviyan P, A Beaulah, KR Rajadurai, T Anitha and KP Sivakumar

The growing world population demands at 70% increase in food production by 2050, requiring measures to reduce substantial Postharvest Losses (PHL) of 28-55% in fruits and vegetables. Artificial Intelligence (AI) technologies offer promising solutions throughout the postharvest supply chain. Harvesting, AI systems can detect, localize, and selectively harvest matured produce using computer vision, and robotics. AI models can evaluate ripeness, detect defects, and grade produce based on quality parameters during sorting, using sensors like RGB cameras and hyper spectral imaging. During storage, AI methodologies such as artificial neural networks, genetic algorithms, and fuzzy logic model changes respiration rate, quality changes, microbial growth, and physiological disorders, facilitating optimal conditions. Smart tracking devices integrating multiple sensors and AI algorithms can monitor and control atmospheric parameters to prevent spoilage. Though implementation requires developing infrastructure and sustainable practices alongside AI integration, these technologies present game-changing opportunities to optimize postharvest operations, reduce waste, and enhance food security for the future.

Published Date: 2026-01-19; Received Date: 2024-11-19