Design and evaluation of a rapid biosensor for dairy pathogen detection

Thesis Abstract

The rapid and accurate detection of pathogenic bacteria in dairy products remains a critical challenge in food safety management, with current methods being time-consuming, labor-intensive, and often requiring complex laboratory infrastructure. This study aims to design, develop, and evaluate a novel biosensor platform capable of delivering real-time detection of key dairy pathogens, including Listeria monocytogenes, Salmonella spp., and Escherichia coli O157H7, thereby addressing delays associated with conventional microbiological assays. The specific objectives are to (1) engineer biosensor components utilizing aptamer-based recognition elements for high specificity, (2) optimize the transduction mechanism through electrochemical impedance spectroscopy (EIS) to enhance sensitivity, and (3) assess the biosensor’s performance in detecting pathogens in dairy samples under laboratory and simulated field conditions. Employing a mixed-methods research design, the study integrates iterative laboratory development with quantitative performance evaluation complemented by qualitative usability assessments. The population of the study comprises dairy samples obtained from ten commercial dairy farms, totaling 150 samples, and laboratory-cultured reference strains of the target pathogens. Sample collection involved aseptic procedures to prevent cross-contamination, and biosensor fabrication incorporated nanomaterial-enhanced electrodes to improve signal transduction. Data collection instruments included standardized microbiological culture methods as the gold standard for validation, alongside electrochemical measurement devices for biosensor signal detection. The validity of the biosensor was established through calibration curves generated via spiked dairy sample analysis, and reliability was confirmed through repeated measures with a coefficient of variation maintained below 5%. Data analysis employed regression analysis to determine detection limits, receiver operating characteristic (ROC) curves to evaluate diagnostic accuracy, and analysis of variance (ANOVA) to compare biosensor performance against traditional methods. Thematic analysis was applied to qualitative usability data to inform device refinement. Expected findings indicate that the biosensor exhibits detection limits below 10^2 CFU/mL for all targeted pathogens, with a response time of less than 30 minutes, significantly outperforming conventional cultural techniques that typically require 24-72 hours. The biosensor is anticipated to demonstrate an accuracy above 95%, with strong correlation coefficients (r > 0.9) with standard microbiological assays. The device is also expected to demonstrate robustness and reproducibility across different dairy matrices, including raw milk, pasteurized milk, and cheese samples. This research contributes novel insights into the integration of nanomaterial-enhanced electrochemical biosensing technology within the dairy food safety sector, offering a rapid, reliable, and user-friendly detection tool suitable for on-site application. It advances existing knowledge by providing empirical validation of aptamer-based electrochemical sensors tailored specifically for dairy pathogen detection, and it lays a foundation for scalable deployment in resource-limited settings. The study's implications extend to improving timely decision-making in dairy safety management and reducing the incidence of foodborne illnesses. The main conclusion emphasizes that the developed biosensor holds significant promise for real-world implementation in dairy quality control, subject to further validation and field trials. The study recommends scaling up the biosensor's production, exploring integration with portable electronic devices for field use, and conducting longitudinal field evaluations to assess operational stability. Future research avenues include expanding the range of detectable pathogens, incorporating multiplexing capabilities, and exploring strategies for cost reduction to facilitate widespread adoption in both industrial and smallholder dairy contexts.