Consumer-oriented smart dynamic detection of fresh food quality: recent advances and future prospects

Abstract

Since fresh foods include a significant amount of water, fat, and protein, it is more likely to become infected by microorganisms causing a major loss of quality. Traditional detection techniques are less able to meet customer expectations owing to the limitations of high cost, slow response time, and inability to permit dynamic monitoring. Intelligent non-destructive detection technologies have emerged in recent years, which offer the advantages of small size and fast response at low cost. However, dynamic monitoring of fresh food quality based on intelligent detection technologies on the consumer side has not been rigorously evaluated yet. This paper discussed the application of intelligent detection technologies based on the consumer side in the dynamic monitoring of fresh food freshness, microorganisms, food additives, and pesticide residues. Furthermore, the application of intelligent detection technologies combined with smartphones for quality monitoring and detection of fresh foods is evaluated. Moreover, the challenges and development trends of intelligent fresh food quality detection technologies are also discussed. Intelligent detection technologies based on the consumer side are designed to detect in real-time the quality of fresh food through visual color changes in combination with smartphones. This paper provides ideas and recommendations for the application of intelligent detection technologies based on the consumer side in food quality detection/monitoring and future research trends.

Keywords:

• Food quality
• fresh food
• intelligent detection technologies
• dynamic monitoring
• consumer

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

Financial support from the National Key R&D Program of China (Contract No. 2022YFD2100601), the Jiangsu Province Key Laboratory Project of Advanced Food Manufacturing Equipment and Technology (No. FMZ202003), and the National First-Class Discipline Program of Food Science and Technology (No. JUFSTR20180205), all of which enabled us to carry out this study.