Optimized hydrogel environment for a tyrosinase-based sandwich-type phenol biosensor: Application of modeling results to real samples

Abstract

This work reports the development and optimization of a tyrosinase-based amperometric biosensor for the detection of oxidizable phenols in tea infusions. The enzyme was immobilized within a hydrogel matrix composed of chitosan and mucin, crosslinked with diluted glutaraldehyde. Response Surface Methodology combined with the Desirability Function was employed to optimize the enzymatic matrix, maximizing sensitivity while minimizing response time. The optimal matrix composition corresponds to 50% chitosan and 50% mucin crosslinked with 5% diluted glutaraldehyde. Different enzyme loadings were evaluated to improve the trade-off between sensitivity and linear range. Experimental and theoretical results indicated that high enzyme loadings enhanced sensitivity but restricted the linear range due to oxygen depletion and promoted phenolic polymerization near the active sites, affecting stability. Conversely, lower loadings provided extended linear ranges with only a minor effect on the detection limit. An enzymatic loading of 13 U/sensor was selected as the best compromise between sensitivity, stability, and cost. The optimized biosensor enabled rapid and reproducible quantification of oxidizable phenols in green tea, black tea, and yerba mate infusions, with analysis times below one hour. Results were consistent with literature values and highlighted the necessity of applying a standard addition method to account for matrix effects.