Miniaturized Electronic Noses for Food Quality and Safety: Applications in Lipid Oxidation Monitoring.

Lipid oxidation is a major degradation process in lipid-rich food systems, producing volatile organic compounds (VOCs) associated with rancidity, off-flavours, and reduced shelf life. Although conventional techniques such as gas chromatography-mass spectrometry (GC-MS) provide reliable identification and quantification of oxidation products, their laboratory-based operation and complex sample preparation limit their suitability for rapid, real-time monitoring. This review examines recent advances in miniaturized and portable electronic-nose (e-nose) systems for monitoring lipid oxidation and food quality through volatile fingerprint analysis. Unlike chromatographic techniques, e-noses generate characteristic response patterns using sensor arrays coupled with pattern recognition and machine learning algorithms rather than directly identifying individual compounds. The relationship between oxidation-derived volatiles, including aldehydes, ketones, alcohols, and hydrocarbons, and e-nose responses are discussed across various food matrices. Metal oxide semiconductor (MOS) sensors remain the most widely investigated technology because of their robustness, scalability, and portability, while electrochemical, conducting polymer, quartz crystal microbalance (QCM), optical, field-effect transistor (FET), and surface acoustic wave (SAW) sensors are also reviewed. Recent developments in chemometric, machine learning, and deep learning approaches for classification, prediction, and sensor-drift compensation are highlighted, alongside applications in edible oils, meat, dairy products, fermented foods, beverages, coffee, and cocoa. Despite considerable progress, sensor drift, humidity interference, calibration transfer, reproducibility, and limited industrial validations remain important challenges. Future research should prioritize sensor stability, standardized validation protocols, and integration with smart-food-monitoring platforms for reliable real-time quality assessment and shelf-life applications.