Microcystins (MCs) are toxins produced by cyanobacteria commonly found in harmful algal blooms (HAB) occurring in many surface waters. Due to their toxicity to humans and other organisms, the World Health Organization (WHO) set a guideline of 1 µg/L for microcystin-leucine-arginine (MC-LR) in drinking water. However, current analytical techniques for the detection of MC-LR such as liquid chromatography-mass spectrometry (LC-MS) and enzyme-linked immunosorbent assay (ELISA) are costly, bulky, time-consuming, and mostly conducted in a laboratory, requiring highly trained personnel. Therefore, an analytical method that can be used in the field for rapid determination is essential. In this study, an Anti-MC-LR/MC-LR/Cysteamine coated screen-printed carbon electrode (SPCE) biosensor was newly developed to detect MC-LR, bioelectrochemically, in water. The functionalization of the electrode surface was examined using scanning electron microscopy-energy dispersive X-Ray spectroscopy (SEM-EDX) and X-Ray photoelectron spectroscopy (XPS). The sensor performance was evaluated by electrochemical impedance spectroscopy (EIS), obtaining a linear working range of MC-LR concentrations between 0.1 and 100 µg/L with a limit of detection (LOD) of 0.69 ng/L. Natural water samples experiencing HABs were then collected and analyzed using the developed biosensor and validated using ELISA, demonstrating the excellent performance of the biosensor with a relative standard deviation (RSD) of 0.65%. The interference and selectivity tests showed a minimal error and RSD values against other common MCs and possible coexisting ions found in water, suggesting high selectivity and low sensitivity of the biosensor. The biosensor showed acceptable functionality with a shelf life of up to 12 weeks. Overall, the Anti-MC-LR/MC-LR/Cysteamine/SPCE biosensors can be an innovative solution with characteristics that allow for in situ, low-cost, and easy-to-use capabilities which are essential for developing an overarching and integrated "smart" environmental management system.
Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-2671 |
Date | 01 January 2022 |
Creators | Stoll, Stephanie |
Publisher | STARS |
Source Sets | University of Central Florida |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Electronic Theses and Dissertations, 2020- |
Page generated in 0.0014 seconds