Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/47152
Title: HUMANN-based system to identify benzimidazole fungicides using multi-synchronous fluorescence spectra: an ensemble approach
Authors: Suárez Araujo, Carmen Paz 
García Báez, Patricio 
Sánchez Rodríguez, Álvaro
Santana Rodríguez, José Juan 
UNESCO Clasification: 120304 Inteligencia artificial
3308 Ingeniería y tecnología del medio ambiente
Keywords: Benzimidazole fungicides
Ensemble system
Environment
Fluorescence spectrometry
HUMANN, et al
Issue Date: 2009
Journal: Analytical and Bioanalytical Chemistry 
Conference: 13th International Symposium on Luminescence Spectrometry 
Abstract: In this paper, we approach, using neural computation and ensemble systems, a pattern classification problem in fluorescence spectrometry, the resolution of difficult multi-fungicide mixtures (overlapping), specifically the benzimidazole fungicides, benomyl, carbendazim, thiabendazole and fuberidazole. These fungicides are compounds of an important environmental interest. Because of this, from an analytical point of view, it is interesting to develop sensitive, selective and simple methods for their determination. Fluorescence spectrometry has proven to be a sensitive and selective technique for determination of many compounds of environmental interest, but in some cases it is not enough. HUMANN is a hierarchical, unsupervised, modular, adaptive neural net with high biological plausibility, which has shown to be suitable for identification of these fungicides and organochlorinated compounds of environmental interest. We propose two modular artificial intelligent systems, with a structure of pre-processing and processing stage, a multi-input HUMANN-based system, using multi-fluorescence spectra as input to the system, and a HUMANN-ensemble system. We analyze the optimal configuration of inputs and the ensemble in order to obtain better results. We study such figures as precision and sensitivity of the method. Our proposal is a smart, flexible and effective complementary method, which allows reducing the analytical and/or computational complexity of the analysis.
URI: http://hdl.handle.net/10553/47152
ISSN: 1618-2642
DOI: 10.1007/s00216-009-2654-7
Source: Analytical and Bioanalytical Chemistry [ISSN 1618-2642], v. 394 (4), p. 1059-1072
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