The use of Artificial Neural Networks for the selective detection of two organophosphate insecticides: chlorpyrifos and chlorfenvinfos.

Amperometric acetylcholinesterase (AChE) biosensors have been developed to resolve mixtures of chlorpyrifos oxon (CPO) and chlorfenvinfos (CFV) pesticides. Three different biosensors were built using the wild type from electric eel (EE), the genetically modified Drosophila melanogaster AChE B394 and B394 co-immobilized with a phosphotriesterase (PTE). Artificial Neural Networks (ANNs) were used to model the combined response of the two pesticides. Specifically two different ANNs were constructed. The first one was used to model the combined response of B394+PTE and EE biosensors and was applied when the concentration of CPO was high and the other, modelling the combined response of B394+PTE and B394 biosensors, was applied with low concentrations of CPO. In both cases, good prediction ability was obtained with correlation coefficients better than 0.986 when the obtained values were compared with those expected for a set of six external test samples not used for training.