Authors
Adam Ee Xian Loh, Kheng Soo Tay
Published in
Methods in molecular biology (Clifton, N.J.). Volume 3043. Pages 269-286.
Abstract
Continuous flow analysis (CFA) offers a robust platform for real-time chemical monitoring and analysis, but the high cost and complexity of commercial systems limit their usage. This chapter describes a practical, low-cost, and reproducible approach for developing a continuous flow colorimetric detection system using open-source electronics, 3D-printed components, and custom data processing software. The setup incorporates a peristaltic pump, an Arduino-controlled solenoid valve, and an AS7341 visible light sensor aligned with a flow-through cuvette. A key innovation of this system is the integration of a Python-based algorithm to process real-time absorbance data and automatically identify and exclude interference-induced signal artifacts. This method enables low-cost detection of colorimetric changes in flowing samples and is particularly suited for biological and chemical analyses involving colorimetric detection, as well as educational settings. The system's modular design allows for easy customization, and its reproducibility makes it useful for dissemination across teaching laboratories or low-resource research environments.
PMID:
42423900
Bibliographic data and abstract were imported from PubMed on 09 Jul 2026.
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