Electronic sensor array coupled with artificial neural network for detection of Salmonella Typhimurium

An electronic sensor array with 12 non-specific metal oxide sensors was evaluated for its ability to monitor volatile compounds in super broth, alone and in super broth inoculated with Salmonella Typhimurium at 37 °C for 2–14 h. Using discriminant function analysis (DFA), it was possible to differentiate super broth alone from that containing Salmonella Typhimurium. The potential to predict the number of Salmonella Typhimurium was investigated using an artificial neural network (ANN). The ANN was comprised of an input layer, one hidden layer and an output layer, with a hyperbolic tangent sigmoidal transfer function in the hidden layer and a linear transfer function in the output layer. Good prediction was found as measured by a regression coefficient (R2 = 0.998) between actual and predicted data.