Analysis of experimental biosensor/fia lactose measurements

Detalhes bibliográficos
Autor(a) principal: Trierweiler, Jorge Otávio
Data de Publicação: 2003
Outros Autores: Ferreira, Luciane da Silveira, Souza Júnior, Maurício Bezerra de, Hitzmann, Bernd, Folly, Rossana Odette Mattos
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFRGS
Texto Completo: http://hdl.handle.net/10183/75863
Resumo: Whey is an abundant effluent in the production of cheese and casein. The biotechnological utilization of this economically important and nutritive source is limited mainly because of the presence of high percentages of lactose. This disaccharide has poor solubility, which can cause crystallization and insufficient sweetness in dairy food; additionally, part of the adult population suffers from associated lactose intolerance diseases. There are several methods to determine lactose such as spectrophotometry, polarimetry, infrared spectroscopy, titrimetry and chromatography. However these methods are tedious and time-consuming due to long sample preparation. These disadvantages stimulated the development of an enzymatic lactose biosensor. It employs two immobilized enzymes, -galactosidase and glucose oxidase and the quantitative analysis of lactose is based on determination of oxygen consumption in the enzymatic reaction. The influence of temperature on the biosensor signal was experimentally studied. It was observed that a nonlinear relationship exists between the electric response of the biosensor – provided by CAFCA (Computer Assisted Flow Control & Analysis - ANASYSCON, Hannover) - and lactose concentration. In this work, attempts were made to correlate these variables using a simple nonlinear model and multilayered neural networks, with the latter providing the best modeling of the experimental data.
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spelling Trierweiler, Jorge OtávioFerreira, Luciane da SilveiraSouza Júnior, Maurício Bezerra deHitzmann, BerndFolly, Rossana Odette Mattos2013-07-16T01:44:57Z20030104-6632http://hdl.handle.net/10183/75863000383680Whey is an abundant effluent in the production of cheese and casein. The biotechnological utilization of this economically important and nutritive source is limited mainly because of the presence of high percentages of lactose. This disaccharide has poor solubility, which can cause crystallization and insufficient sweetness in dairy food; additionally, part of the adult population suffers from associated lactose intolerance diseases. There are several methods to determine lactose such as spectrophotometry, polarimetry, infrared spectroscopy, titrimetry and chromatography. However these methods are tedious and time-consuming due to long sample preparation. These disadvantages stimulated the development of an enzymatic lactose biosensor. It employs two immobilized enzymes, -galactosidase and glucose oxidase and the quantitative analysis of lactose is based on determination of oxygen consumption in the enzymatic reaction. The influence of temperature on the biosensor signal was experimentally studied. It was observed that a nonlinear relationship exists between the electric response of the biosensor – provided by CAFCA (Computer Assisted Flow Control & Analysis - ANASYSCON, Hannover) - and lactose concentration. In this work, attempts were made to correlate these variables using a simple nonlinear model and multilayered neural networks, with the latter providing the best modeling of the experimental data.application/pdfengBrazilian journal of chemical engineering. São Paulo, SP. Vol. 20, n. 1 (2003), p. 7-13BiossensoresLactoseBiosensorFIANeural networksβ-galactosidaseAnalysis of experimental biosensor/fia lactose measurementsinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/otherinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSORIGINAL000383680.pdf000383680.pdfTexto completo (inglês)application/pdf135587http://www.lume.ufrgs.br/bitstream/10183/75863/1/000383680.pdfbc0354660a148a45f0050e9071ba0065MD51TEXT000383680.pdf.txt000383680.pdf.txtExtracted Texttext/plain14744http://www.lume.ufrgs.br/bitstream/10183/75863/2/000383680.pdf.txtb3129b1b92f2da7176655da95b96a317MD52THUMBNAIL000383680.pdf.jpg000383680.pdf.jpgGenerated Thumbnailimage/jpeg1621http://www.lume.ufrgs.br/bitstream/10183/75863/3/000383680.pdf.jpgf90d2952d458bb337d9f809953026573MD5310183/758632018-10-16 09:28:44.956oai:www.lume.ufrgs.br:10183/75863Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2018-10-16T12:28:44Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false
dc.title.pt_BR.fl_str_mv Analysis of experimental biosensor/fia lactose measurements
title Analysis of experimental biosensor/fia lactose measurements
spellingShingle Analysis of experimental biosensor/fia lactose measurements
Trierweiler, Jorge Otávio
Biossensores
Lactose
Biosensor
FIA
Neural networks
β-galactosidase
title_short Analysis of experimental biosensor/fia lactose measurements
title_full Analysis of experimental biosensor/fia lactose measurements
title_fullStr Analysis of experimental biosensor/fia lactose measurements
title_full_unstemmed Analysis of experimental biosensor/fia lactose measurements
title_sort Analysis of experimental biosensor/fia lactose measurements
author Trierweiler, Jorge Otávio
author_facet Trierweiler, Jorge Otávio
Ferreira, Luciane da Silveira
Souza Júnior, Maurício Bezerra de
Hitzmann, Bernd
Folly, Rossana Odette Mattos
author_role author
author2 Ferreira, Luciane da Silveira
Souza Júnior, Maurício Bezerra de
Hitzmann, Bernd
Folly, Rossana Odette Mattos
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Trierweiler, Jorge Otávio
Ferreira, Luciane da Silveira
Souza Júnior, Maurício Bezerra de
Hitzmann, Bernd
Folly, Rossana Odette Mattos
dc.subject.por.fl_str_mv Biossensores
Lactose
topic Biossensores
Lactose
Biosensor
FIA
Neural networks
β-galactosidase
dc.subject.eng.fl_str_mv Biosensor
FIA
Neural networks
β-galactosidase
description Whey is an abundant effluent in the production of cheese and casein. The biotechnological utilization of this economically important and nutritive source is limited mainly because of the presence of high percentages of lactose. This disaccharide has poor solubility, which can cause crystallization and insufficient sweetness in dairy food; additionally, part of the adult population suffers from associated lactose intolerance diseases. There are several methods to determine lactose such as spectrophotometry, polarimetry, infrared spectroscopy, titrimetry and chromatography. However these methods are tedious and time-consuming due to long sample preparation. These disadvantages stimulated the development of an enzymatic lactose biosensor. It employs two immobilized enzymes, -galactosidase and glucose oxidase and the quantitative analysis of lactose is based on determination of oxygen consumption in the enzymatic reaction. The influence of temperature on the biosensor signal was experimentally studied. It was observed that a nonlinear relationship exists between the electric response of the biosensor – provided by CAFCA (Computer Assisted Flow Control & Analysis - ANASYSCON, Hannover) - and lactose concentration. In this work, attempts were made to correlate these variables using a simple nonlinear model and multilayered neural networks, with the latter providing the best modeling of the experimental data.
publishDate 2003
dc.date.issued.fl_str_mv 2003
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10183/75863
dc.identifier.issn.pt_BR.fl_str_mv 0104-6632
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dc.relation.ispartof.pt_BR.fl_str_mv Brazilian journal of chemical engineering. São Paulo, SP. Vol. 20, n. 1 (2003), p. 7-13
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