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Portable Multispectral Imaging System for Sodium Nitrite Detection via Griess Reaction on Cellulose Fiber Sample Pads
Chanwit Kataphiniharn1, Nawapong Unsuree2, Suwatwong Janchaysang2
1Department of Industrial Physics and Medical Instrumentation, Faculty of Applied Science, King Mongkut's University of Technology North Bangkok, Bangkok 10800, Thailand.
Sensors (Basel, Switzerland)
|December 11, 2025
Summary
A portable multispectral imaging (MSI) system with computer vision accurately detects sodium nitrite using the Griess reaction. The normalized difference index (NDI) derived from MSI data significantly improves detection accuracy over traditional methods.
Area of Science:
- Analytical Chemistry
- Spectroscopy
- Chemical Sensing
Background:
- The Griess reaction is a common method for detecting nitrite ions.
- Paper-based substrates offer a low-cost platform for chemical sensing.
- Existing methods for nitrite detection may lack portability or accuracy.
Purpose of the Study:
- To develop and validate a portable multispectral imaging (MSI) system for sensitive sodium nitrite detection.
- To investigate the spectral characteristics of nitrite-induced azo dyes on paper substrates.
- To enhance detection accuracy using a normalized difference index (NDI) approach.
Main Methods:
- A custom-built portable MSI system (360-940 nm) was integrated with computer vision.
- Sodium nitrite detection was performed using the Griess reaction on para-aminobenzoic acid (PABA) and sulfanilamide (SA) substrates.
- Spectral absorption was analyzed, and a normalized difference index (NDI) was calculated using optimal spectral bands.
- Performance was evaluated against varying illumination and compared with smartphone RGB imaging.
Main Results:
- MSI images showed increased absorption (darker regions) with higher sodium nitrite concentrations.
- The NDI, calculated from MSI data, demonstrated a stronger correlation with nitrite concentration than single spectral bands.
- NDI improved the coefficient of determination (R² ) by ~19-20% for both PABA-NED and SA-NED substrates.
- The MSI-based NDI significantly outperformed conventional smartphone RGB imaging.
Conclusions:
- The portable MSI system offers a robust, rapid, and non-destructive method for on-site chemical analysis.
- The NDI framework enhances image interpretability and enables effective data analysis for chemical detection.
- This approach provides a practical guideline for developing advanced, portable chemical sensing systems.

