A Comprehensive Review of Artificial Intelligence Applications in Postharvest Engineering

Abstract

Artificial Intelligence (AI) has emerged as a transformative force in the field of agriculture, especially in postharvest engineering where timely and accurate decision-making significantly affects product quality and economic outcomes. This review synthesizes the current advancements in AI applications across postharvest stages, including harvesting, grading, sorting, storage, transportation, and supply chain optimization. The study examines various AI techniques such as machine learning (ML), deep learning (DL), computer vision, and robotics, while also discussing existing challenges and future directions. Our review indicates that AI can significantly reduce postharvest losses, improve product traceability, and contribute to sustainable agricultural practices.