A smartphone-integrated paper-based colorimetric sensor array: Real-time detection and classification of flavonoids.

Area of Science:

• Analytical Chemistry
• Biosensor Technology
• Food Science

Background:

• Flavonoid-rich Citrus herbal products (FRCHPs) are widely used but require reliable authentication methods.
• Existing methods for FRCHP analysis can be time-consuming, expensive, or lack portability.
• Developing rapid, accurate, and accessible detection techniques is crucial for quality control.

Purpose of the Study:

• To develop a smartphone-integrated paper-based colorimetric sensor array (PBCSA) for distinguishing various FRCHPs.
• To optimize the sensor array and analytical model for enhanced efficiency and accuracy.
• To create a practical, real-time detection system for FRCHPs.

Main Methods:

• Fabrication of a 3x3 PBCSA using inkjet printing with a hydrophobic barrier.
• Application of indicator displacement assay strategy for flavonoid detection.
• Optimization of the sensor array using Genetic Algorithm and Support Vector Machine (SVM).
• Integration of the optimized SVM model with a custom mobile application for real-time analysis.

Main Results:

• The PBCSA successfully distinguished between different species and concentrations of flavonoids and FRCHPs.
• Optimization reduced the sensor units from nine to five, achieving 100.00% accuracy.
• The integrated SVM and mobile app enabled real-time, practical detection of FRCHPs.
• The developed system demonstrated broad applicability for FRCHP analysis.

Conclusions:

• A novel, smartphone-integrated PBCSA offers a simple, economical, and efficient approach for FRCHP authentication.
• The indicator displacement assay and SVM optimization strategy are effective for sensor array development.
• This technology significantly enhances the practicability of real-time analysis for herbal products.