Optical biosensor advances for real-time food safety

A team from Dibrugarh University reports that optical biosensors are moving from lab prototypes to practical tools for tracking pathogens, toxins, pesticides, antibiotics, and heavy metals across the food chain. The review maps what works today, what blocks wider use, and where the field is heading.

The paper, titled Advancements in Optical Biosensor Technology for Food Safety and Quality Assurance, appears in Engineering Proceedings. It is a proceedings article that consolidates recent results, methods, and policy context for deployment.

What do these sensors do, and why do they matter for food safety?

Optical biosensors translate a specific biological recognition event into a measurable light signal. Common recognition events include antigen–antibody binding and nucleic acid hybridization. Readouts include fluorescence, chemiluminescence, absorbance, and surface plasmon resonance. The approach delivers high sensitivity and specificity, fast results, and supports on-site testing across farms, plants, and markets.

The review points to several advantages that align with urgent food safety needs. These devices detect trace levels of harmful substances and return results quickly, which helps prevent contaminated food from moving down the supply chain. Their portability cuts cost and turnaround time compared with conventional lab methods, which is valuable in low-resource settings.

Coverage spans the main hazard groups that regulators and industry track: foodborne pathogens such as Salmonella, Listeria monocytogenes, and E. coli; microbial toxins including staphylococcal enterotoxins and botulinum toxin; chemical hazards such as pesticide residues, heavy metals, and antibiotic residues; and quality markers tied to freshness and shelf life.

As food safety programs move closer to the point of processing and consumption, the field is trending toward compact lab-on-chip formats that integrate light sources, detectors, and microfluidics. Smartphone readers and battery-powered units enable rapid testing in markets and warehouses. This supports real-time decisions and early action.

The review also tracks a shift from single-analyte checks to multiplex analysis. New optical platforms can screen for multiple contaminants in one assay, which is key when several hazards may co-occur in complex food matrices. Integration with connected systems enables traceability, remote access, and cloud analytics throughout the supply chain.

Which technologies lead, and how do they work in practice?

The paper organizes platforms into several core classes: surface plasmon resonance, localized SPR, fiber-optic SPR, interferometric, surface-enhanced Raman, surface-enhanced fluorescence, total internal reflection, fluorescence, chemiluminescence, and colorimetric sensors. Each class couples a bio-recognition layer with a distinct optical readout to turn binding events into signals that can be measured and compared.

Mechanisms differ but share a clear thread. SPR tracks refractive index shifts at a metal–dielectric interface during binding. Fluorescence and luminescence approaches measure emission changes when labeled molecules bind to targets. Interferometric sensors detect phase shifts tied to mass or refractive index changes. The paper underlines that design choices in the recognition chemistry and in the optics together determine sensitivity and reliability.

In applied settings, SPR platforms deliver label-free, real-time detection for pathogens and contaminants. Interferometric sensors support high-throughput multiplex screening. SERS boosts weak Raman signals to reach very low detection limits. Colorimetric formats provide simple visual readouts for field checks. Fiber-optic variants improve sensitivity in complex liquids like milk and juice. Together, these options cover routine screening for microbial threats, toxins, pesticides, antibiotic residues, and metals across grains, beverages, dairy, produce, and processed foods.

Performance gains increasingly come from materials and data. Nanomaterials such as quantum dots, carbon dots, gold nanoparticles, graphene, and metal–organic frameworks raise signal strength and stability. At the system level, microfluidics speeds sample handling. On the software side, machine learning supports denoising, feature extraction, and timely decisions. The review notes that these threads are converging into intelligent, connected monitoring platforms.

Another growth path is networked sensing. Internet-connected biosensors linked to cloud systems enable continuous traceability across the supply chain and support early warnings for contamination events.

What blocks routine use, and what must happen next?

Despite technical maturity, three hurdles slow broad adoption. First, complex food matrices can degrade performance through non-specific interactions and interferences. This limits specificity at ultra-low concentrations and can cause false results without careful surface chemistry and coatings. Second, reproducibility across diverse foods remains difficult, and many platforms are still at prototype stage. Third, validation and regulatory alignment are incomplete.

Regulatory agencies require rigorous method validation on par with established laboratory techniques. The paper explains that the absence of harmonized international protocols slows recognition by the U.S. Food and Drug Administration, the European Food Safety Authority, and the Codex Alimentarius Commission. Until common benchmarks exist for accuracy, reproducibility, and safety, market entry will remain uneven.

Costs and usability also matter. Production and scale-up increase price, while end users need devices that are easy to operate in busy industrial settings. Sustainable business models have to balance performance, price, and demand to move beyond pilot trials.

The authors outline a practical path forward. Advances in nanomaterials, plasmonic enhancement, and microfabrication should continue to push sensitivity and miniaturization. Multiplex formats can cut time and cost per sample while capturing co-occurring hazards. IoT links and cloud analytics can add traceability and predictive risk alerts. In parallel, standards bodies and regulators need shared validation rules that translate strong lab results into accepted field methods.

The potential payoff is large. Integrated platforms promise rapid, ultra-sensitive, and portable detection at critical points in the chain from farm to fork. That can reduce outbreaks, strengthen consumer protection, and support food security, especially where laboratory infrastructure is limited.