Portable Multispectral Imaging System for Sodium Nitrite Detection via Griess Reaction on Cellulose Fiber Sample Pads
1
Issued Date
2025-12-01
Resource Type
eISSN
14248220
Scopus ID
2-s2.0-105024637234
Pubmed ID
41374703
Journal Title
Sensors
Volume
25
Issue
23
Rights Holder(s)
SCOPUS
Bibliographic Citation
Sensors Vol.25 No.23 (2025)
Suggested Citation
Kataphiniharn C., Unsuree N., Janchaysang S., Lumjeak S., Tulyananda T., Wangkham T., Srichola P., Nithiwutratthasakul T., Chattham N., Phanphak S. Portable Multispectral Imaging System for Sodium Nitrite Detection via Griess Reaction on Cellulose Fiber Sample Pads. Sensors Vol.25 No.23 (2025). doi:10.3390/s25237323 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/113608
Title
Portable Multispectral Imaging System for Sodium Nitrite Detection via Griess Reaction on Cellulose Fiber Sample Pads
Corresponding Author(s)
Other Contributor(s)
Abstract
This study presents a custom-built, portable multispectral imaging (MSI) system integrated with computer vision for sodium nitrite detection via the Griess reaction on paper-based substrates. The MSI system was used to investigate the absorption characteristics of sodium nitrite at concentrations from 0 to 10 ppm across nine spectral bands spanning 360–940 nm on para-aminobenzoic acid (PABA) and sulfanilamide (SA) substrates. Upon forming azo dyes with N-(1-naphthyl) ethylenediamine (NED), the PABA and SA substrates exhibited strong absorption near 545 nm and 540 nm, respectively, as measured by a spectrometer. This agrees with the 550 nm MSI images, in which higher sodium nitrite concentration regions appeared darker due to increased absorption. A concentration-correlation analysis was conducted for each spectral band. The normalized difference index (NDI), constructed from the most and least correlated bands at 550 nm and 940 nm, showed a stronger correlation with sodium nitrite concentration than the single best-performing band for both substrates. The NDI increased the coefficient of determination (R<sup>2</sup>) by approximately 19.32% for PABA–NED and 19.89% for SA–NED. This improvement was further confirmed under varying illumination conditions and through comparison with a conventional smartphone RGB imaging approach, in which the MSI-based NDI showed substantially superior performance. The enhancement is attributed to improved contrast, illumination normalization by the NDI, and the narrower spectral bands of the MSI compared with RGB imaging. In addition, the NDI framework enabled effective image segmentation, classification, and visualization, improving both interpretability and usability and providing a practical guideline for developing more robust models with larger training datasets. The proposed MSI system offers strong advantages in portability, sub-minute acquisition time, and operational simplicity, enabling rapid, on-site, and non-destructive chemical analysis.