Gas sensor technologies and mathematical modelling for quality sensing in fruit and vegetable cold chains: A review

Background: Fruit and vegetable (F&V) harvested from plants trigger a series of stress-related physiological processes, potentially resulting in quality deterioration and considerable losses. Cold chain acting as abiotic stressors and activation of specific pathways to maintains metabolic activities is an effective way to reduce postharvest F&V loss. To this end, real-time monitoring of the micro-environment of the cold chain is an important approach. While temperature and humidity are routinely monitored nowadays, gas is much less explored despite it deeply interacts with the product quality of cold chain. Scope and approach: This article analyzes the requirement for quality sensing via gas signal, reviews existing and emerging gas sensor technology and gas signal processing method for F&V cold chain. Furthermore, mathematical models, which interpret sensed gas data and predict product quality, are systematically analyzed and discussed.. Key findings and conclusions: Gas sensor technology and associated modelling method is an effective approach to improve transparency and product quality for F&V cold chain. The results illustrate that the gas sensor for quality sensing of F&V cold chain should have characteristic with high precise resolution and full scale, low power consumption, low cost and smaller size, existed gas sensors have been gradually developed from a single unit to a plurality of components, specially rigid and flexible structural materials and manufacturing process. Existing mathematical models still have limited prediction accuracy that gas signal interfere product quality. Then, the model need improve the performances to explain the complex interaction relationship between gas and quality.

Automated summary

This article discusses the importance of quality sensing in F&V cold chain through gas signal, and reviews existing and emerging gas sensor technology, gas signal processing methods, and the application of mathematical models. The findings suggest that gas sensor technology is effective in improving transparency and product quality in F&V cold chain, but existing mathematical models still have limited prediction accuracy and need further improvement to explain the complex interaction between gas and product quality.