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The freshness of food directly affects the quality, safety, and taste of food. Traditional freshness monitoring methods often involve time-consuming processes and complex operations that struggle to meet the need for rapid and real-time detection. With the industrialization of food, the complexity of production, storage, and transportation of staple foods has increased, further increasing the need for efficient freshness monitoring technologies. At present, the development of visual monitoring technology is relatively mature, but its application in the field of staple food has not yet formed a system. This review focuses on food visualization monitoring technologies, particularly their potential applications in monitoring the freshness of staple foods. This article delves into key technologies such as pH-responsive systems, colorimetric sensors, and fluorescence sensing techniques and explores their integration with smart packaging and machine learning. These techniques can effectively detect spoilage-related substances with high sensitivity and accuracy. When integrated with smart packaging and machine learning, their efficiency and reliability can be further improved. Although these technologies perform excellently in terms of sensitivity and accuracy, they still face issues such as cost, stability, and safety in practical applications. This paper systematically evaluates existing technologies with the aim of exploring the future development directions of staple food freshness monitoring technologies, providing new insights for the development of efficient, accurate, and economically feasible food quality control methods.
Xu et al. (Wed,) studied this question.