Multivariate data analysis of dynamic amperometric biosensor responses from binary analyte mixtures—application of sensitivity correction algorithms

摘要: Abstract In this paper, it is demonstrated that a single-receptor biosensor can be used to quantitatively determine each analyte in binary mixtures using multivariate data analysis tools based on the dynamic responses received from flow injection peaks. Mixtures with different concentrations of two phenolic compounds, catechol and 4-chlorophenol, were measured graphite electrode modified tyrosinase enzyme at an applied potential −50 mV versus Ag/AgCl. A correction algorithm measurements references in-between samples was compensate for ageing as well differences caused by deviations between preparations. After correction, relative prediction errors partial least squares regression (PLS-R) 4-chlorophenol 7.4 5.5%, respectively, sequence one biosensor. Additional validation phenols new biosensor, prepared same procedure but batch enzyme. Using mixture first sensor calibration set PLS-R, mixtures, after applying procedures, 7.0% 16.0% 4-chlorophenol. These preliminary results indicate algorithms could possible use less stable biosensors continuous on-line together without time-consuming procedures.