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Metadados | Descrição | Idioma |
---|---|---|
Autor(es): dc.creator | Nunes, Lidiane Cristina | - |
Autor(es): dc.creator | Silva, Gilmare Antônia da | - |
Autor(es): dc.creator | Trevizan, Lilian Cristina | - |
Autor(es): dc.creator | Santos Júnior, Dario | - |
Autor(es): dc.creator | Poppi, Ronei Jesus | - |
Autor(es): dc.creator | Krug, Francisco José | - |
Data de aceite: dc.date.accessioned | 2019-11-06T13:33:26Z | - |
Data de disponibilização: dc.date.available | 2019-11-06T13:33:26Z | - |
Data de envio: dc.date.issued | 2015-04-14 | - |
Data de envio: dc.date.issued | 2015-04-14 | - |
Data de envio: dc.date.issued | 2009 | - |
Fonte completa do material: dc.identifier | http://www.repositorio.ufop.br/handle/123456789/5074 | - |
Fonte: dc.identifier.uri | http://educapes.capes.gov.br/handle/capes/558015 | - |
Descrição: dc.description | 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. | - |
Idioma: dc.language | en | - |
Direitos: dc.rights | O Periódico Spectrochimica Acta Part B: Atomic Spectroscopy concede permissão para depósito deste artigo no Repositório Institucional da UFOP. Número da licença: 3580760144309. | - |
Palavras-chave: dc.subject | Plant analysis | - |
Palavras-chave: dc.subject | Genetic algorithm | - |
Palavras-chave: dc.subject | Simultaneous optimization | - |
Palavras-chave: dc.subject | Bayesian regularized neural network | - |
Palavras-chave: dc.subject | Laser induced breakdown spectroscopy | - |
Título: dc.title | Simultaneous optimization by neuro-genetic approach for analysis of plant materials by laser induced breakdown spectroscopy. | - |
Aparece nas coleções: | Repositório Institucional - UFOP |
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