<p>Accurate quality assessment of fruits and vegetables is essential to modern agriculture and the food industry, supporting food safety, minimizing post-harvest losses, meeting market demands, and ensuring consumer trust and satisfaction. Conventional methods, while effective, are often destructive, labour-intensive, and time-consuming. In recent years, Electronic Nose (E-nose) technology has emerged as a powerful, non-invasive alternative, capable of mimicking the human olfactory system to detect volatile organic compounds (VOCs) related to ripeness, freshness, spoilage, and contamination. This review provides a comprehensive synthesis of the evolution, operating principles, sensor types, and practical applications of E-nose systems in fruit and vegetable quality evaluation. It explores a variety of sensor platforms, including Metal Oxide Semiconductor (MOS), MQ-based sensors, Quartz Crystal Microbalance (QCM), mass spectrometry-based, portable, and SPME-integrated systems, and examines their principle for fruit and vegetable quality evaluation. Furthermore, the paper reviewed the integration of E-nose systems with machine learning algorithms for assessing fruit and vegetable quality. By mapping both technological progress and existing limitations, this review provides a valuable reference for researchers, technologists, and stakeholders aiming to implement E-nose solutions in fruit and vegetable quality monitoring systems.</p>