ReviewFoods (Basel, Switzerland)2026
Microfluidics-Integrated Spectroscopic Technologies for Food Safety and Quality Assessment: From Complex-Matrix Processing to On-Site Decision-Making.
Review in Foods (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Food safety and quality analysis is shifting from laboratory-based end-point testing toward faster, lower-volume and matrix-adapted on-site decision-making. Near-infrared (NIR), visible-near-infrared (Vis-NIR), hyperspectral, Raman, surface-enhanced Raman scattering (SERS), fluorescence, colorimetric and terahertz approaches, together with impedance time-series readout, provide complementary information on composition, molecular vibrations, spatial distribution, reaction outputs, or electrical responses. In real foods, however, lipids, proteins, sugars, salts, pigments, particles and native fluorescence can alter spectral baselines, mass transfer and model stability. The value of microfluidics is therefore not limited to miniaturization but lies in organizing filtration, homogenization, splitting, mixing, extraction, enrichment, reaction, and readout positions into a controllable sample-to-signal workflow. This review first distinguishes chemical hazards, biological hazards, authenticity issues, and quality changes according to target and matrix characteristics, and then compares the functional boundaries of continuous-flow, paper-based, droplet, digital-hybrid and enrichment-oriented chips. It further analyses how microfluidics affects detection time, sample and reagent consumption, sensitivity, selectivity, repeatability, portability and cross-matrix applicability through spectral interfaces, signal enhancement, labelled and label-free detection, chemometrics, and machine learning. Representative applications involving pesticides, mycotoxins, pathogens, antibiotics, heavy metals, adulterants, oxidation products, and freshness indicators in real foods are discussed within a unified chain linking chip architecture, spectral signal generation and decision models. Finally, requirements for translation are proposed in terms of standard and real samples, chip-to-chip variation, external model validation, data traceability and scalable manufacturing, providing an operational framework for the joint design of broad-spectrum spectroscopic technologies and microfluidic systems.
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Registered trials
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.