Portable Multispectral Imaging System for Sodium Nitrite Detection via Griess Reaction on Cellulose Fiber Sample Pads

dc.contributor.authorKataphiniharn C.
dc.contributor.authorUnsuree N.
dc.contributor.authorJanchaysang S.
dc.contributor.authorLumjeak S.
dc.contributor.authorTulyananda T.
dc.contributor.authorWangkham T.
dc.contributor.authorSrichola P.
dc.contributor.authorNithiwutratthasakul T.
dc.contributor.authorChattham N.
dc.contributor.authorPhanphak S.
dc.contributor.correspondenceKataphiniharn C.
dc.contributor.otherMahidol University
dc.date.accessioned2025-12-20T18:31:00Z
dc.date.available2025-12-20T18:31:00Z
dc.date.issued2025-12-01
dc.description.abstractThis 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.
dc.identifier.citationSensors Vol.25 No.23 (2025)
dc.identifier.doi10.3390/s25237323
dc.identifier.eissn14248220
dc.identifier.pmid41374703
dc.identifier.scopus2-s2.0-105024637234
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/123456789/113608
dc.rights.holderSCOPUS
dc.subjectChemistry
dc.subjectBiochemistry, Genetics and Molecular Biology
dc.subjectComputer Science
dc.subjectComputer Science
dc.subjectPhysics and Astronomy
dc.subjectEngineering
dc.titlePortable Multispectral Imaging System for Sodium Nitrite Detection via Griess Reaction on Cellulose Fiber Sample Pads
dc.typeArticle
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105024637234&origin=inward
oaire.citation.issue23
oaire.citation.titleSensors
oaire.citation.volume25
oairecerif.author.affiliationKasetsart University
oairecerif.author.affiliationKing Mongkut's University of Technology North Bangkok
oairecerif.author.affiliationFaculty of Science, Mahidol University
oairecerif.author.affiliationChulachomklao Royal Military Academy

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