Discrimination of soils and assessment of soil fertility using information from an ion selective electrodes array and artificial neural networks
Mimendia Sancho, Aitor (Universitat Autònoma de Barcelona. Departament de Química)
Gutiérrez Salgado, Juan Manuel (Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional. Departamento de Ingeniería Eléctrica)
Alcañiz, Josep M. (Josep Maria)
(Universitat Autònoma de Barcelona. Departament de Biologia Animal, de Biologia Vegetal i d'Ecologia)
Valle Zafra, Manuel del (Universitat Autònoma de Barcelona. Departament de Química)
Fecha: |
2014 |
Resumen: |
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. |
Ayudas: |
Ministerio de Ciencia e Innovación CTQ2010-17099
|
Derechos: |
Tots els drets reservats. |
Lengua: |
Anglès |
Documento: |
Article ; recerca ; Versió sotmesa a revisió |
Materia: |
Electronic tongue ;
Organic matter ;
Pattern recognition ;
Soil analysis ;
Soil sensing |
Publicado en: |
CLEAN, Vol. 42, Issue 12 (Dec. 2014) , p. 1808-1815, ISSN 1863-0669 |
DOI: 10.1002/clen.201300923
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Registro creado el 2015-12-15, última modificación el 2023-10-04