SENSING CHARACTERISTICS AND MATHEMATICAL MODELLING OF PLANT TISSUE POLYPHENOLASE SENSORS

Abstract

Dopamine, a neurotransmitter is commonly associated with Parkinson's disease, neural crest tumour and the stupor characteristics of drug addicts. It is oxidised in the presence of polyphenol oxidase, an enzyme commonly found in plant tissues. Its kinetics was studied by monitoring the concentration of the reaction product, 2,3-dihydroindole-5,6 quinone, at 470 nm in a spectrophotometer. The data were successfully correlated by the rate equation for a proposed mechanism. This reaction was used as a basis for dopamine sensing. The sensor was prepared by overlaying a dissolved oxygen probe with a biofilm containing pretreated tissue powder of apple, potato, banana or mushroom. During the pretreatment, the tissue was fragmented, exposed to air, washed with water, vacuum dried and pulverised to a fine powder. These sensors showed significantly higher sensitivity (0.0248-0.0347 µA µ,M-1 ), lower concentration detection limits (0.58-0.81 µM), better reproducibility, stability and remarkably longer service life (>2-5 months) than those prepared without the same pretreatment by other workers. The good sensing characteristics can be attributed to the removal of the biodegradable solutes from the tissue during pretreatment. The pH for optimum response varied within 5.56-7.40 depending on the source material and fabrication of the biofilm. The sensor selectivity for dopamine was improved considerably by coating the biofilm with a Nafion film. The Nafion-coating effectively precluded neutral and anionic solutes from entering the biofilm. The addition of the Nafion- coating did not affect stability and reproducibility of the sensors and service life was further improved to longer than 7 months involving 300-500 measurements. The Nafion-coated apple sensor showed better selectivity to dopamine compared with other Nafion-coated tissue sensors. Its response in a mixture containing dopamine and three major interferents ( arterenol, histidine and tyrosine) was linear with respect to the concentration of each of the solutes. The sensitivity of each of the components in the mixture was higher than the corresponding single component linear range sensitivity. A theoretical model was developed to relate the steady-state and transient sensor response to the rate processes occurring in the system. The experimental data of apple, potato, banana and mushroom sensors were correlated according to the analytical solution of the steady-state model and numerical solution of the transient-state model. A significant feature of the proposed procedure for the regression of the transient response data involved predetermining the steady-state model parameters. This approach reduced the number of unknown parameters involving in the transient model from six to two. Altogether 405 steady-state data and 34911 transient data were used for the verification of the models. The good correlation of the experimental data by the steady-state and transient models and prediction by the transient model confirmed their adequacy in describing the sensing behaviour of tissue sensors at different pH, mass of tissue powder and temperature.