Document Detail

Monitoring substrate and products in a bioprocess with FTIR spectroscopy coupled to artificial neural networks enhanced with a genetic-algorithm-based method for wavelength selection.
MedLine Citation:
PMID:  18970424     Owner:  NLM     Status:  In-Data-Review    
An experiment was developed as a simple alternative to existing analytical methods for the simultaneous quantitation of glucose (substrate) and glucuronic acid (main product) in the bioprocesses Kombucha by using FTIR spectroscopy coupled to multivariate calibration (partial least-squares, PLS-1 and artificial neural networks, ANNs). Wavelength selection through a novel ranked regions genetic algorithm (RRGA) was used to enhance the predictive ability of the chemometric models. Acceptable results were obtained by using the ANNs models considering the complexity of the sample and the speediness and simplicity of the method. The accuracy on the glucuronic acid determination was calculated by analysing spiked real fermentation samples (recoveries ca. 115%).
Vanina G Franco; Juan C Perín; Víctor E Mantovani; Héctor C Goicoechea
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Publication Detail:
Type:  Journal Article     Date:  2005-08-10
Journal Detail:
Title:  Talanta     Volume:  68     ISSN:  1873-3573     ISO Abbreviation:  Talanta     Publication Date:  2006 Jan 
Date Detail:
Created Date:  2008-10-30     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  2984816R     Medline TA:  Talanta     Country:  England    
Other Details:
Languages:  eng     Pagination:  1005-12     Citation Subset:  -    
Laboratorio de Control de Calidad de Medicamentos, Cátedra de Química Analítica I, Facultad de Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral, Ciudad Universitaria, Santa Fe, Argentina.
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