Evidence map›Paper›PMID 42550294›Full record

ReviewMikrochimica acta2026

Smartphone-based optical and spectroscopic sensors for food safety monitoring: principles, applications, and future directions.

Nguyen Ngoc Nghia, Tran Dang Khoa, Nguyen Phuong Bao Han, Nguyen Thuy Diem Thao, Phan Quang Huy Hoang, Nguyen Huu Hieu

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In one paragraph

Review in Mikrochimica acta, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Nguyen Ngoc NghiaKey Laboratory of Chemical Engineering and Petroleum Processing (Key CEPP Lab), VNU-HCM, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, Dien Hong Ward, Ho Chi Minh City, Vietnam.
Tran Dang KhoaKey Laboratory of Chemical Engineering and Petroleum Processing (Key CEPP Lab), VNU-HCM, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, Dien Hong Ward, Ho Chi Minh City, Vietnam.
Nguyen Phuong Bao HanKey Laboratory of Chemical Engineering and Petroleum Processing (Key CEPP Lab), VNU-HCM, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, Dien Hong Ward, Ho Chi Minh City, Vietnam.
Nguyen Thuy Diem ThaoKey Laboratory of Chemical Engineering and Petroleum Processing (Key CEPP Lab), VNU-HCM, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, Dien Hong Ward, Ho Chi Minh City, Vietnam.
Phan Quang Huy HoangKey Laboratory of Chemical Engineering and Petroleum Processing (Key CEPP Lab), VNU-HCM, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, Dien Hong Ward, Ho Chi Minh City, Vietnam.
Nguyen Huu HieuKey Laboratory of Chemical Engineering and Petroleum Processing (Key CEPP Lab), VNU-HCM, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, Dien Hong Ward, Ho Chi Minh City, Vietnam. nhhieubk@hcmut.edu.vn.ORCID https://orcid.org/0000-0003-1776-9871

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Food safety monitoring increasingly requires analytical tools that are rapid, portable, and accessible beyond centralized laboratories. In this context, smartphone-based optical and spectroscopic sensors have emerged as highly promising platforms because they combine image acquisition, signal processing, data transmission, and user-friendly interfaces within a compact and widely available device. This review critically summarizes recent advances in smartphone-enabled food safety sensing, with emphasis on the underlying optical principles, hardware integration strategies, analytical workflows, and application scenarios. We discuss the major sensing modalities currently adapted to smartphone platforms, including colorimetric, fluorescence, chemiluminescence, and Raman/surface-enhanced Raman scattering approaches, and examine how camera modules, illumination control, add-on optics, 3D-printed attachments, and app-based processing pipelines influence analytical performance. Recent applications are organized by target class, covering pesticide residues, heavy metals, mycotoxins, adulterants, microbial pathogens, and spoilage-related markers. Across these categories, smartphone-assisted systems have demonstrated strong potential for decentralized screening, field deployment, and point-of-need decision support. However, the transition from laboratory demonstrations to practical deployment remains constrained by unresolved issues related to analytical standardization, validation under realistic food conditions, and integration of smartphone hardware with reliable data-processing workflows. Emerging trends indicate that future progress will be driven by artificial intelligence-assisted analysis, multimodal sensing, sustainable substrates, smart packaging integration, and connectivity with cloud- and traceability-based digital food systems. Overall, smartphone-based optical and spectroscopic sensors are evolving from low-cost imaging tools into increasingly sophisticated analytical platforms with the potential to bridge laboratory-grade detection and real-world food safety surveillance.

Indexed as

Biosensing TechniquesFood SafetySmartphoneColorimetryFood ContaminationSpectrum Analysis, RamanFood contaminantsFood safetyOptical sensingPoint-of-need detectionSmartphone-based biosensorsSpectroscopic sensing

Identifiers

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.