Multivariate data analysis of impedimetric biosensor responses from Salmonella typhimurium

Abstract

A multivariate data analysis was performed on responses of an impedimetric biosensor to quantify Salmonella typhimurium. To develop the impedimetric biosensor, an interdigitated microelectrode (IME) was fabricated by using a semiconductor fabrication process. Anti-Salmonella antibodies were immobilized based on streptavidin–biotin binding on the surface of the IME to form an active sensing layer. The impedance spectra of the biosensor were measured at frequencies ranging between 10 Hz and 1 MHz with different concentrations of S. typhimurium in PBS and pork samples. Partial-least squares (PLS) regression models were developed and evaluated as a multivariate data analysis method. The best PLS regression model developed from impedance spectra that were acquired with different individual biosensors had the correlation coefficient of determination (R²) 0.75 and 0.59 for PBS and pork samples, respectively. The PLS models estimated the concentration of S. typhimurium with 1.49 and 1.96 Log CFU mL⁻¹ of root mean square of error in prediction (RMSEP) for PBS and pork samples, respectively. The PLS model built with impedance data from the same biosensor improved R² to 0.85 and 0.89, and reduced the RMSEPs to 1.13 and 1.02 Log CFU mL⁻¹ for PBS and pork samples, respectively. This study showed the feasibility of quantifying S. typhimurium by performing multivariate analysis on responses from the impedimetric biosensor.