Paper-Based Colorimetric Assays Using Chitosan-Immobilized Enzymes and RGB Analysis for Glucose, Cholesterol, and Dopamine Quantification
Year: 2026
Type: article
Abstract: Paper-based colorimetric assays offer a low-complexity strategy for transforming enzymatic reactions into measurable optical responses. In this study, individual colorimetric assays for glucose, cholesterol, and dopamine were evaluated using glucose oxidase (GOx), cholesterol oxidase (ChOx), and monoamine oxidase A (MAO-A) immobilized on chitosan macrospheres. Immobilization efficiencies of 79%, 70%, and 70% were obtained for GOx, ChOx, and MAO-A, respectively, with saturation times of 20 min for GOx and ChOx and 10 min for MAO-A. The enzymatic reactions generated concentration-dependent chromatic responses under controlled laboratory conditions. Color measurements were performed under standardized instrumental conditions and expressed using CIE XYZ tristimulus coordinates, while the Euclidean distance relative to the corresponding blank was used as the analytical response. Glucose showed an approximately linear response over the evaluated calibration range, whereas cholesterol exhibited a nonlinear saturation behavior and was described using an exponential saturation model. For dopamine, quantitative linear calibration was restricted to the low-concentration region using the non-blank standards. The limits of detection were 32.01 mg/dL for glucose, 1.62 mg/dL for cholesterol, and 0.00047 µg/mL for dopamine, with corresponding limits of quantification of 96.99 mg/dL, 4.91 mg/dL, and 0.00142 µg/mL, respectively. The results demonstrate the feasibility of combining chitosan-immobilized enzymes, paper-supported chromogenic reactions, and quantitative color analysis for the individual determination of glucose, cholesterol, and dopamine under controlled laboratory conditions. A paper-based microfluidic architecture is additionally proposed as a proof-of-concept for the future integration of the individually characterized assays.
Source: Eng—Advances in Engineering
DOI: 10.3390/eng7090436
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,448
OpenAlex ID: W7204916457