An intelligent sensing system for thermal processing contaminants via decoding nucleophilic reactivity fingerprints...

Area of Science:

• Food Chemistry
• Analytical Chemistry
• Biosensors

Background:

• Thermal processing can generate hazardous foodborne carcinogens, including chloropropanols and glycidol.
• Current detection methods for these contaminants are complex, time-consuming, and require laboratory settings.

Purpose of the Study:

• To develop an intelligent sensing system for rapid and accurate detection and quantification of chloropropanols and glycidol.
• To create a robust platform for on-site food safety analysis.

Main Methods:

• A nanozyme-based sensor array was designed to decode the nucleophilic reactivity fingerprints of contaminants.
• A dual-task feature selection framework optimized the sensor array from 15 to 6 elements.
• The system leverages the specific restoration of nanozyme activity by contaminants.

Main Results:

• The system achieved high-throughput identification (F1 score > 0.95) and precise quantification (R² > 0.99) of individual and mixed contaminants.
• Demonstrated robustness in complex food matrices (soy sauce, biscuit, edible oil) with high accuracy (R² > 0.98).
• Enabled accurate quantification with simple sample preparation.

Conclusions:

• The developed intelligent sensing system offers a novel approach for precision food safety.
• This platform integrates chemical principles with artificial intelligence for on-site decision-making.
• Provides a high-performance, adaptable solution for detecting foodborne carcinogens.