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Enhancing food safety and quality: multiplex detection using smart nanostructured molecular logic technologies.

Xinru Yu^1,2,3, Hongbin Pu^1,2,3, Da-Wen Sun^1,2,3,4

¹School of Food Science and Engineering, South China University of Technology, Guangzhou, China.

Critical Reviews in Food Science and Nutrition

|October 14, 2025

Summary

Smart nanostructured molecular logic technologies (SNMLT) offer advanced multi-target detection for food safety. This review highlights SNMLT

Keywords:

Nanostructured molecular logic food safety multiplex detection smart sensing

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Area of Science:

Food analysis and safety
Nanotechnology in sensing
Molecular logic systems

Background:

Multi-target detection is crucial for comprehensive food safety and quality assessment.
Smart nanostructured molecular logic technologies (SNMLT) are emerging for multiplex food analysis.
Component materials-based SNMLT show promise due to rapid response, multifunctionality, and high sensitivity.

Purpose of the Study:

To provide a comprehensive review of SNMLT sensing platforms for food multi-target detection.
To summarize the principles, classification, component materials, and signal output strategies of SNMLT.
To highlight the applications of SNMLT in detecting physical, biological, and chemical hazards in food.

Main Methods:

Review of existing literature on SNMLT for food analysis.
Description of SNMLT operational principles and classification.
Summary of component materials and signal output mechanisms.
Analysis of SNMLT applications in various food safety contexts.

Main Results:

SNMLT offers a wide detection range and strong anti-interference capabilities for multiplex assays.
Component materials-based SNMLT are effective for simultaneous analysis of multiple food analytes.
Applications span physical, biological, and chemical hazard detection, as well as food quality assessment.

Conclusions:

SNMLT presents a powerful platform for advanced food safety monitoring.
Future research should focus on integrating SNMLT with artificial intelligence for user-friendly sensing devices.
Further development is needed to address challenges and enhance the practical application of SNMLT in food analysis.