Tercer informe anual sobre inmigración e integración

Comunicación de la Comisión al Consejo, al Parlamento Europeo, al Comité Económico y Social y al Comité de las Regiones. Bruselas, 11.9.2007 COM (2007) 512 final

Glyphosate detection by voltammetric techniques. A comparison between statistical methods and an artificial neural network

Glyphosate quantification methods are complex and expensive, and its control in natural water bodies is getting more important year after year. In order to find a new system that facilitates the detection of glyphosate, we present a comparison between two models to predict glyphosate concentration in aqueous dissolutions. One of them is done by an artificial neural network (ANN) embedded in a microcontroller and the other one is done by statistic methods (Partial Least Squares) in a computer. From an analytical point of view, voltammetric techniques have been selected to obtain electrochemical responses to different glyphosate concentrations. In order to get them, a voltammetry/amperometry device designed by our research group and called FraPlus has been used. In this work we have selected two sensitive electrodes (cobalt and copper), 10 different glyphosate concentrations and a train pulse made by nine different voltammetric pulses to build the models. The ANN developed model is able to properly relate data obtained by FraPlus and glyphosate concentrations and the obtained value for regression coefficient (R) is 0.9998 and the P-value is 0.0. Taking into account these results, we propose this ANN model based in voltammetric techniques working with glyphosate concentrations in a buffer as an approach to glyphosate detection in natural water bodies.Authors acknowledge financial support from the Universitat Politecnica de Valencia and its Centre de Cooperacio al Desenvolupament (Programa ADSIDEO-COOPERACIO 2010) for the research fellowship and support given by UNIJUI University & Staff during the stage of Prof. Laguarda in Ijui (RS-Brazil). We also thank MICINN (MAT2009-14564-C04-02) and GVA (PPC/2011/019) for their respective research fellowships.Laguarda-Miro, N.; Werner Ferreira, F.; Garcia-Breijo, E.; Ibáñez Civera, FJ.; Gil Sánchez, L.; Garrigues Baixauli, J. (2012). Glyphosate detection by voltammetric techniques. A comparison between statistical methods and an artificial neural network. Sensors and Actuators B: Chemical. 171-172:528-536. https://doi.org/10.1016/j.snb.2012.05.025S528536171-17

El planteamiento global sobre la migración un año después: hacia una política global europea en materia de migración

Comunicación de la Comisión al Consejo y al Parlamento Europeo, Bruselas, 30.11.2006 COM (2006) 735 final