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Biosensors Based on Phenol Oxidases (Laccase, Tyrosinase, and Their Mixture) for Estimating the Total Phenolic Index in Food-Related Samples

Summary

This review discusses specialized sensors that can quickly measure the total amount of beneficial plant compounds (phenolics) in foods like tea, wine, coffee, and fruits. These biosensors use enzymes from mushrooms and other sources to detect phenolic compounds more efficiently than traditional methods. The sensors can be made more effective by using tiny materials called nanomaterials, which improve how well they work and how long they last.

Background

Plant phenolic compounds demonstrate significant bioactive properties with approximately 9000 identified phenolic substances. Determining individual phenolic compounds is complex, making total phenolic content (TPC) assessment more practical for routine analyses. Biosensors based on phenol oxidases have emerged as alternative analytical devices for detecting phenolic compounds in food and vegetal matrices.

Objective

To comprehensively review phenol oxidase-based biosensors using laccase and tyrosinase for estimating total phenolic index (TPI) in food-related samples. The review addresses enzymatic and bienzymatic sensor development, nanomaterial functions, immobilization techniques, and validation methods for TPI assessment.

Results

The review describes laccase and tyrosinase catalytic properties and their application in enzymatic and bienzymatic biosensors. Nanomaterials improve biosensor performance through nano-immobilization, electron transfer, signal formation, and amplification. Both optical (fluorescent and colorimetric) and electrochemical (potentiometric, voltammetric, amperometric) biosensors were developed with limits of detection ranging from 0.01 to 10 μM.

Conclusion

Phenol oxidase-based biosensors represent viable alternatives for TPI estimation in food-related samples. Removal of ascorbic acid and use of highly purified enzymes are recommended strategies for reducing interference. Novel immobilization methods and nanomaterial integration show promise for improving long-term biosensor stability and performance in routine food quality control.
  • Published in:Life (Basel),
  • Study Type:Review,
  • Source: PMID: 36836650, PMC9964280, DOI: 10.3390/life13020291
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