Smart Technologies for Post-harvest Processing and Monitoring

This collection, "Smart Technologies for Post-harvest Processing and Monitoring", systematically explores the integration of advanced technological innovations to optimize post-harvest management of agricultural products. It specifically focuses on advancing research in IoT-enabled environmental sensing, AI-driven process optimization, machine learning-based quality analytics, and non-invasive detection systems (e.g., hyperspectral imaging, electromagnetic sensors). The call emphasizes scalable solutions that address critical challenges in post-harvest efficiency, product degradation, and safety assurance, with particular attention to energy-efficient storage systems, automated quality grading platforms, and data-driven shelf-life prediction models. Submissions are encouraged to highlight cross-disciplinary advancements—such as electromagnetic/non-thermal preservation techniques, blockchain-integrated traceability frameworks, and edge computing for decentralized monitoring—that bridge theoretical innovation with industrial applicability. Case studies targeting climate-resilient systems, smallholder farmer support, and resource-limited settings are prioritized to demonstrate global relevance. By fostering collaboration between food scientists, engineers, and data specialists, this issue aims to deliver actionable insights for reducing post-harvest losses, enhancing food security , and advancing sustainable agri-food ecosystems.

Keywords: IoT, Artificial Intelligence, Machine Learning, Sensor Technology, Automation, Post-harvest Technology, Smart Storage, Real-time Monitoring, Food Quality, Food Safety, Agricultural Produce, Predictive Modeling, Data-driven Processing, Electromagnetic Radiation, Non-thermal Processing.