Feasibility of the use of disposable optical tongue based on neural networks for heavy metal identification and determination

This study presents the development and characterization of a disposable optical tongue for the simultaneous identification and determination of the heavy metals Zn(II), CLIO and Ni(II). The immobilization of two chromogenic reagents, 1-(2-pyridylazo)-2-naphthol and Zincon, and their arrangement forms an array of membranes that work by complexation through a co-extraction equilibrium, producing distinct changes in color in the presence of heavy metals. The color is measured from the image of the tongue acquired by a scanner working in transmission mode using the H parameter (hue) of the HSV color space, which affords robust and precise measurements. The use of artificial neural networks (ANNs) in a two-stage approach based on color parameters, the H feature of the array, makes it possible to identify and determine the analytes. In the first stage, the metals present above a threshold of 10(-7) M are identified with 96% success, regardless of the number of metals present, using the H feature of the two membranes. The second stage reuses the H features in combination with the results of the classification procedure to estimate the concentration of each analyte in the solution with acceptable error. Statistical tests were applied to validate the model over real data, showing a high correlation between the reference and predicted heavy metal ion concentration. (C) 2013 Elsevier B.V. All rights reserved.