Mimendia A., Gutierrez J.M., Alcaniz J.M., del Valle M. (0) Discrimination of Soils and Assessment of Soil Fertility Using Information from an Ion Selective Electrodes Array and Artificial Neural Networks. Clean - Soil, Air, Water. 42: 1808-1815.EnllaçDoi: 10.1002/clen.201300923
Multichannel sensor measurements combined with advanced treatment is the departure point for a new concept in sensorics, the electronic tongue. Our setup worked with an array of 20 ion selective electrodes plus an artificial neural network used as a pattern recognition method applied to soil analysis. With this design, we got a versatile tool which was able to perform qualitative and quantitative determinations. As first application, the qualitative discrimination between six distinct soil types based on their extractable components was attempted. The procedure was simplified to a single extraction step before measurements. Water, a BaCl2 saline solution and an acetic acid extract were evaluated as extracting agents. The best performance was reached with the acetic acid extraction method with a correct classification rate and sensitivity both of 94%, and a specificity of 100%. In addition, a quantitative determination of several physicochemical properties of agricultural interest, such as organic carbon content and selected cations (like K+ or Mg2+) and anions (like NO3 - or Cl-) was also demonstrated, showing satisfactory agreement with the reference methods. An electronic tongue system - the new approach in chemical analysis consisting of multidimensional sensor signals plus computer processing tools - showed the ability in distinguishing six distinct soil types in a first qualitative application example. A quantitative model demonstrated the correct estimation of selected cations (K+, Mg2+), anions (NO3 -, Cl-) plus the organic carbon content.
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