Automated flow based biosensor for quantification of binary organophosphates mixture in milk using artificial neural network
Résumé
This work presents an application of automatic flow based biosensor to detect binary (chlorpyriphos-oxon (CPO) and malaoxon (MO)) organophosphate (OP) mixtures in milk, based on artificial neural network (ANN). Genetically modified acetylcholinesterase (AChE) B394 and B4 were used as a biological recognition element for sensor development. AChE binds with OPs irreversibly, creating an anionic phosphonyl species. The enzymes were coupled on screen printed electrodes (SPEs) and inserted in a flow cell connected to the potentiostat and syringe pump. In order to model the combined response of CPO and MO, a total set of 19 mixtures were prepared using ANN. The modeling was validated with an external test of 6 milk samples spiked with CPO and MO mixtures. The spiked concentrations of CPO and MO were ranged from 5 × 10−10 to 5 × 10−12 M and 1.01 × 10−10 to 9.17 × 10−11 M, respectively. These concentrations were determined using factorial designing (FD) method and the obtained and expected recovery values in milk showed good co-relation. The average % recovery yields for CPO and MO are 109.53 and 100.66, respectively.