Recognition of ochratoxins by a host-guest ratiometric fluorescent sensor array

Area of Science:

• Analytical Chemistry
• Food Science
• Biochemistry

Background:

• Ochratoxins are mycotoxins that pose significant risks to food safety and public health.
• Accurate and sensitive detection methods for ochratoxins in various food matrices are essential.

Purpose of the Study:

• To develop a novel binary ratiometric fluorescent sensor array for the identification and differentiation of ochratoxins in food.
• To utilize pattern recognition methods for analyzing fluorescence data and achieving accurate ochratoxin detection.

Main Methods:

• Development of a binary ratiometric fluorescent sensor array utilizing albumin (ALB) and dye assembly.
• Detection of ochratoxins based on their binding to albumin, leading to displacement of fluorescent dyes and modulation of fluorescence signals.
• Application of pattern recognition techniques including Linear Discriminant Analysis (LDA), Hierarchical Cluster Analysis (HCA), and Support Vector Machine (SVM) for data analysis.
• Validation of the sensor array using fluorescence and RGB modes for discriminating ochratoxin types and concentrations.

Main Results:

• The sensor array successfully generated unique fluorescence fingerprints for different ochratoxins.
• Accurate discrimination between three types of ochratoxins and their concentrations was achieved.
• The array demonstrated effective identification of ochratoxins and their mixtures in real food samples like flour and millet.
• The developed method showed high sensitivity and specificity in ochratoxin detection.

Conclusions:

• A novel and effective binary ratiometric fluorescent sensor array has been developed for ochratoxin detection in food.
• The sensor array, coupled with pattern recognition, provides a powerful tool for differentiating ochratoxins and their mixtures.
• This methodology offers a valuable approach for monitoring ochratoxin contamination and advancing the study of mycotoxin biotransformation.