Investigation of NIR spectra pre-processing methods combined with multivariate regression for determination of moisture in powdered industrial egg

Detalhes bibliográficos
Autor(a) principal: Watanabe, Lycio Shinji
Data de Publicação: 2018
Outros Autores: Bovolenta, Yuri Renan, Acquaro Junior, Vinicius Ricardo, Barbin, Douglas Fernandes, Madeira, Tiago Bervelieri, Nixdorf, Suzana Lucy
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Acta scientiarum. Technology (Online)
Texto Completo: http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/30133
Resumo:  High productivity and meantime perishability of in natura eggs, make powdered egg attractive for patisseries and pasta industries. Water reduction in 65%, extends shelf life from 1 to 12 months, preventing also Salmonella. Maximum powdered egg moisture allowed by Brazilian law is 6.0%  (w w-1). However, its determination by reference technique (oven at 105ºC for 8 hour) is lengthy for processing industry. Therefore, the purpose of this study was to investigate the influence of several spectral pre-processing techniques in the application of near-infrared spectroscopy associated with chemometrics models for determination of moisture content in powdered egg, without the need of sample preparation and destruction, held at 0.5 min. Several pre-treatment techniques were evaluated to ensure spectral data reliability such as: standard normal variation; multiplicative scatter correction; smoothing and detrend. The principal component regression (PCR) and partial least squares (PLS) were evaluated with and without pre-treatment. The best results were observed in NIR/PLS model (49 samples), providing an adequate correlation (r) of 0.96, for cross-validation. Using 21 samples as prediction set, NIR/PLS showed relative error (RE) < 2.0%, compared to primary methods oven and thermobalance, indicating to be suitable for industrial quality control.
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spelling Investigation of NIR spectra pre-processing methods combined with multivariate regression for determination of moisture in powdered industrial eggchemometricsnear-infrared spectroscopy (NIRS)thermobalanceoven reference methodcalibration modelPLS.Química Analítica High productivity and meantime perishability of in natura eggs, make powdered egg attractive for patisseries and pasta industries. Water reduction in 65%, extends shelf life from 1 to 12 months, preventing also Salmonella. Maximum powdered egg moisture allowed by Brazilian law is 6.0%  (w w-1). However, its determination by reference technique (oven at 105ºC for 8 hour) is lengthy for processing industry. Therefore, the purpose of this study was to investigate the influence of several spectral pre-processing techniques in the application of near-infrared spectroscopy associated with chemometrics models for determination of moisture content in powdered egg, without the need of sample preparation and destruction, held at 0.5 min. Several pre-treatment techniques were evaluated to ensure spectral data reliability such as: standard normal variation; multiplicative scatter correction; smoothing and detrend. The principal component regression (PCR) and partial least squares (PLS) were evaluated with and without pre-treatment. The best results were observed in NIR/PLS model (49 samples), providing an adequate correlation (r) of 0.96, for cross-validation. Using 21 samples as prediction set, NIR/PLS showed relative error (RE) < 2.0%, compared to primary methods oven and thermobalance, indicating to be suitable for industrial quality control.Universidade Estadual De Maringá2018-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionAnálise espectroscópicaapplication/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/3013310.4025/actascitechnol.v40i1.30133Acta Scientiarum. Technology; Vol 40 (2018): Publicação Contínua; e30133Acta Scientiarum. Technology; v. 40 (2018): Publicação Contínua; e301331806-25631807-8664reponame:Acta scientiarum. Technology (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMenghttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/30133/pdfCopyright (c) 2017 Acta Scientiarum. Technologyinfo:eu-repo/semantics/openAccessWatanabe, Lycio ShinjiBovolenta, Yuri RenanAcquaro Junior, Vinicius RicardoBarbin, Douglas FernandesMadeira, Tiago BervelieriNixdorf, Suzana Lucy2019-07-17T11:53:47Zoai:periodicos.uem.br/ojs:article/30133Revistahttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/indexPUBhttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/oai||actatech@uem.br1807-86641806-2563opendoar:2019-07-17T11:53:47Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM)false
dc.title.none.fl_str_mv Investigation of NIR spectra pre-processing methods combined with multivariate regression for determination of moisture in powdered industrial egg
title Investigation of NIR spectra pre-processing methods combined with multivariate regression for determination of moisture in powdered industrial egg
spellingShingle Investigation of NIR spectra pre-processing methods combined with multivariate regression for determination of moisture in powdered industrial egg
Watanabe, Lycio Shinji
chemometrics
near-infrared spectroscopy (NIRS)
thermobalance
oven reference method
calibration model
PLS.
Química Analítica
title_short Investigation of NIR spectra pre-processing methods combined with multivariate regression for determination of moisture in powdered industrial egg
title_full Investigation of NIR spectra pre-processing methods combined with multivariate regression for determination of moisture in powdered industrial egg
title_fullStr Investigation of NIR spectra pre-processing methods combined with multivariate regression for determination of moisture in powdered industrial egg
title_full_unstemmed Investigation of NIR spectra pre-processing methods combined with multivariate regression for determination of moisture in powdered industrial egg
title_sort Investigation of NIR spectra pre-processing methods combined with multivariate regression for determination of moisture in powdered industrial egg
author Watanabe, Lycio Shinji
author_facet Watanabe, Lycio Shinji
Bovolenta, Yuri Renan
Acquaro Junior, Vinicius Ricardo
Barbin, Douglas Fernandes
Madeira, Tiago Bervelieri
Nixdorf, Suzana Lucy
author_role author
author2 Bovolenta, Yuri Renan
Acquaro Junior, Vinicius Ricardo
Barbin, Douglas Fernandes
Madeira, Tiago Bervelieri
Nixdorf, Suzana Lucy
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Watanabe, Lycio Shinji
Bovolenta, Yuri Renan
Acquaro Junior, Vinicius Ricardo
Barbin, Douglas Fernandes
Madeira, Tiago Bervelieri
Nixdorf, Suzana Lucy
dc.subject.por.fl_str_mv chemometrics
near-infrared spectroscopy (NIRS)
thermobalance
oven reference method
calibration model
PLS.
Química Analítica
topic chemometrics
near-infrared spectroscopy (NIRS)
thermobalance
oven reference method
calibration model
PLS.
Química Analítica
description  High productivity and meantime perishability of in natura eggs, make powdered egg attractive for patisseries and pasta industries. Water reduction in 65%, extends shelf life from 1 to 12 months, preventing also Salmonella. Maximum powdered egg moisture allowed by Brazilian law is 6.0%  (w w-1). However, its determination by reference technique (oven at 105ºC for 8 hour) is lengthy for processing industry. Therefore, the purpose of this study was to investigate the influence of several spectral pre-processing techniques in the application of near-infrared spectroscopy associated with chemometrics models for determination of moisture content in powdered egg, without the need of sample preparation and destruction, held at 0.5 min. Several pre-treatment techniques were evaluated to ensure spectral data reliability such as: standard normal variation; multiplicative scatter correction; smoothing and detrend. The principal component regression (PCR) and partial least squares (PLS) were evaluated with and without pre-treatment. The best results were observed in NIR/PLS model (49 samples), providing an adequate correlation (r) of 0.96, for cross-validation. Using 21 samples as prediction set, NIR/PLS showed relative error (RE) < 2.0%, compared to primary methods oven and thermobalance, indicating to be suitable for industrial quality control.
publishDate 2018
dc.date.none.fl_str_mv 2018-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Análise espectroscópica
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/30133
10.4025/actascitechnol.v40i1.30133
url http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/30133
identifier_str_mv 10.4025/actascitechnol.v40i1.30133
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/30133/pdf
dc.rights.driver.fl_str_mv Copyright (c) 2017 Acta Scientiarum. Technology
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2017 Acta Scientiarum. Technology
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Estadual De Maringá
publisher.none.fl_str_mv Universidade Estadual De Maringá
dc.source.none.fl_str_mv Acta Scientiarum. Technology; Vol 40 (2018): Publicação Contínua; e30133
Acta Scientiarum. Technology; v. 40 (2018): Publicação Contínua; e30133
1806-2563
1807-8664
reponame:Acta scientiarum. Technology (Online)
instname:Universidade Estadual de Maringá (UEM)
instacron:UEM
instname_str Universidade Estadual de Maringá (UEM)
instacron_str UEM
institution UEM
reponame_str Acta scientiarum. Technology (Online)
collection Acta scientiarum. Technology (Online)
repository.name.fl_str_mv Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM)
repository.mail.fl_str_mv ||actatech@uem.br
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