Simultaneous optimization by neuro-genetic approach for analysis of plant materials by laser induced breakdown spectroscopy.

A simultaneous optimization strategy based on a neuro-genetic approach is proposed for selection of laser induced breakdown spectroscopy operational conditions for the simultaneous determination of macronutrients (Ca, Mg and P), micro-nutrients (B, Cu, Fe, Mn and Zn), Al and Si in plant samples. A l...

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Detalles Bibliográficos
Autores: Nunes, Lidiane Cristina, Silva, Gilmare Antônia da, Trevizan, Lilian Cristina, Santos Júnior, Dario, Poppi, Ronei Jesus, Krug, Francisco José
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2009
País:Brasil
Institución:Universidade Federal de Ouro Preto (UFOP)
Repositorio:Repositório Institucional da UFOP
Idioma:inglés
OAI Identifier:oai:repositorio.ufop.br:123456789/5074
Acceso en línea:http://www.repositorio.ufop.br/handle/123456789/5074
https://doi.org/10.1016/j.sab.2009.05.002
Access Level:acceso abierto
Palabra clave:Plant analysis
Genetic algorithm
Simultaneous optimization
Bayesian regularized neural network
Laser induced breakdown spectroscopy
Descripción
Sumario:A simultaneous optimization strategy based on a neuro-genetic approach is proposed for selection of laser induced breakdown spectroscopy operational conditions for the simultaneous determination of macronutrients (Ca, Mg and P), micro-nutrients (B, Cu, Fe, Mn and Zn), Al and Si in plant samples. A laser induced breakdown spectroscopy system equipped with a 10 Hz Q-switched Nd:YAG laser (12 ns, 532 nm, 140 mJ) and an Echelle spectrometer with intensified coupled-charge device was used. Integration time gate, delay time, amplification gain and number of pulses were optimized. Pellets of spinach leaves (NIST 1570a) were employed as laboratory samples. In order to find a model that could correlate laser induced breakdown spectroscopy operational conditions with compromised high peak areas of all elements simultaneously, a Bayesian Regularized Artificial Neural Network approach was employed. Subsequently, a genetic algorithm was applied to find optimal conditions for the neural network model, in an approach called neuro-genetic. A single laser induced breakdown spectroscopy working condition that maximizes peak areas of all elements simultaneously, was obtained with the following optimized parameters: 9.0 μs integration time gate, 1.1 μs delay time, 225 (a.u.) amplification gain and 30 accumulated laser pulses. The proposed approach is a useful and a suitable tool for the optimization process of such a complex analytical problem.