Multi-product multivariate calibration: determination of quality parameters in soybean industrialized juices

Detalhes bibliográficos
Autor(a) principal: Santos, Dayane Aparecida dos
Data de Publicação: 2019
Outros Autores: Lima, Karen Priscila de, Consolin, Marcilene Ferrari Barriquello, Consolin Filho, Nelson, Março, Paulo Henrique, Valderrama, Patrícia
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/37382
Resumo: Total acidity and vitamin C were determined by using ultraviolet spectroscopy and multi-product multivariate calibration alternately to the reference methods, the potentiometry and Tillman's, respectively. In the developed multi-products models, different products were included (industrialized juices based on soya of different flavors and light). The linear partial least squares (PLS) method was used in the model construction and the outlier samples were evaluated. The accuracy at the 99% level, represented by the root mean square error of calibration (RMSEC) and prediction (RMSEP), was confirmed through the confidence ellipse, whereas the residuals presented random behavior, which indicates that the data fit a linear model. Sensitivity and analytical sensitivity presented adequate results in the determination of vitamin C and acidity, considering the concentration range used 0.83-16.83 mg 100 mL-1 for vitamin C and 0.17-0.34 g 100 mL-1 for total acidity. The inverse of the analytical sensitivity shows that it is possible to distinguish samples with difference in vitamin C concentration of the order of 0.73 mg 100 mL-1, and samples with difference in total acidity of the order of 6.1 x 10-3 g 100 mL- 1.The multi-product PLS model present limits of detection and quantification for vitamin C of 2.43 and 7.36 mg 100 mL-1, respectively. For total acidity, the limits of detection and quantification achieved were 0.02 and 0.06 mg 100 mL-1, respectively. The values for residual prediction deviation (RPD) presented results within the range of values, which classify the models as satisfactory. In addition, the multi-product calibration is fast, because it does not require reagents/solvents and does not generate toxic waste, being an alternative to the conventional methods and being in agreement with the requirements of green chemistry.
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spelling Multi-product multivariate calibration: determination of quality parameters in soybean industrialized juicesacidityvitamin Cultraviolet spectroscopymulti-product calibrationfigures of meritsoybean juicesTotal acidity and vitamin C were determined by using ultraviolet spectroscopy and multi-product multivariate calibration alternately to the reference methods, the potentiometry and Tillman's, respectively. In the developed multi-products models, different products were included (industrialized juices based on soya of different flavors and light). The linear partial least squares (PLS) method was used in the model construction and the outlier samples were evaluated. The accuracy at the 99% level, represented by the root mean square error of calibration (RMSEC) and prediction (RMSEP), was confirmed through the confidence ellipse, whereas the residuals presented random behavior, which indicates that the data fit a linear model. Sensitivity and analytical sensitivity presented adequate results in the determination of vitamin C and acidity, considering the concentration range used 0.83-16.83 mg 100 mL-1 for vitamin C and 0.17-0.34 g 100 mL-1 for total acidity. The inverse of the analytical sensitivity shows that it is possible to distinguish samples with difference in vitamin C concentration of the order of 0.73 mg 100 mL-1, and samples with difference in total acidity of the order of 6.1 x 10-3 g 100 mL- 1.The multi-product PLS model present limits of detection and quantification for vitamin C of 2.43 and 7.36 mg 100 mL-1, respectively. For total acidity, the limits of detection and quantification achieved were 0.02 and 0.06 mg 100 mL-1, respectively. The values for residual prediction deviation (RPD) presented results within the range of values, which classify the models as satisfactory. In addition, the multi-product calibration is fast, because it does not require reagents/solvents and does not generate toxic waste, being an alternative to the conventional methods and being in agreement with the requirements of green chemistry.Universidade Estadual De Maringá2019-05-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioncalibração multivariadaapplication/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/3738210.4025/actascitechnol.v41i2.37382Acta Scientiarum. Technology; Vol 41 (2019): Publicação Contínua; e37382Acta Scientiarum. Technology; v. 41 (2019): Publicação Contínua; e373821806-25631807-8664reponame:Acta scientiarum. Technology (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMenghttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/37382/pdfCopyright (c) 2019 Acta Scientiarum. Technologyhttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessSantos, Dayane Aparecida dosLima, Karen Priscila deConsolin, Marcilene Ferrari BarriquelloConsolin Filho, NelsonMarço, Paulo HenriqueValderrama, Patrícia2019-07-17T11:54:33Zoai:periodicos.uem.br/ojs:article/37382Revistahttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/indexPUBhttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/oai||actatech@uem.br1807-86641806-2563opendoar:2019-07-17T11:54:33Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM)false
dc.title.none.fl_str_mv Multi-product multivariate calibration: determination of quality parameters in soybean industrialized juices
title Multi-product multivariate calibration: determination of quality parameters in soybean industrialized juices
spellingShingle Multi-product multivariate calibration: determination of quality parameters in soybean industrialized juices
Santos, Dayane Aparecida dos
acidity
vitamin C
ultraviolet spectroscopy
multi-product calibration
figures of merit
soybean juices
title_short Multi-product multivariate calibration: determination of quality parameters in soybean industrialized juices
title_full Multi-product multivariate calibration: determination of quality parameters in soybean industrialized juices
title_fullStr Multi-product multivariate calibration: determination of quality parameters in soybean industrialized juices
title_full_unstemmed Multi-product multivariate calibration: determination of quality parameters in soybean industrialized juices
title_sort Multi-product multivariate calibration: determination of quality parameters in soybean industrialized juices
author Santos, Dayane Aparecida dos
author_facet Santos, Dayane Aparecida dos
Lima, Karen Priscila de
Consolin, Marcilene Ferrari Barriquello
Consolin Filho, Nelson
Março, Paulo Henrique
Valderrama, Patrícia
author_role author
author2 Lima, Karen Priscila de
Consolin, Marcilene Ferrari Barriquello
Consolin Filho, Nelson
Março, Paulo Henrique
Valderrama, Patrícia
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Santos, Dayane Aparecida dos
Lima, Karen Priscila de
Consolin, Marcilene Ferrari Barriquello
Consolin Filho, Nelson
Março, Paulo Henrique
Valderrama, Patrícia
dc.subject.por.fl_str_mv acidity
vitamin C
ultraviolet spectroscopy
multi-product calibration
figures of merit
soybean juices
topic acidity
vitamin C
ultraviolet spectroscopy
multi-product calibration
figures of merit
soybean juices
description Total acidity and vitamin C were determined by using ultraviolet spectroscopy and multi-product multivariate calibration alternately to the reference methods, the potentiometry and Tillman's, respectively. In the developed multi-products models, different products were included (industrialized juices based on soya of different flavors and light). The linear partial least squares (PLS) method was used in the model construction and the outlier samples were evaluated. The accuracy at the 99% level, represented by the root mean square error of calibration (RMSEC) and prediction (RMSEP), was confirmed through the confidence ellipse, whereas the residuals presented random behavior, which indicates that the data fit a linear model. Sensitivity and analytical sensitivity presented adequate results in the determination of vitamin C and acidity, considering the concentration range used 0.83-16.83 mg 100 mL-1 for vitamin C and 0.17-0.34 g 100 mL-1 for total acidity. The inverse of the analytical sensitivity shows that it is possible to distinguish samples with difference in vitamin C concentration of the order of 0.73 mg 100 mL-1, and samples with difference in total acidity of the order of 6.1 x 10-3 g 100 mL- 1.The multi-product PLS model present limits of detection and quantification for vitamin C of 2.43 and 7.36 mg 100 mL-1, respectively. For total acidity, the limits of detection and quantification achieved were 0.02 and 0.06 mg 100 mL-1, respectively. The values for residual prediction deviation (RPD) presented results within the range of values, which classify the models as satisfactory. In addition, the multi-product calibration is fast, because it does not require reagents/solvents and does not generate toxic waste, being an alternative to the conventional methods and being in agreement with the requirements of green chemistry.
publishDate 2019
dc.date.none.fl_str_mv 2019-05-02
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
calibração multivariada
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/37382
10.4025/actascitechnol.v41i2.37382
url http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/37382
identifier_str_mv 10.4025/actascitechnol.v41i2.37382
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/37382/pdf
dc.rights.driver.fl_str_mv Copyright (c) 2019 Acta Scientiarum. Technology
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2019 Acta Scientiarum. Technology
https://creativecommons.org/licenses/by/4.0
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 41 (2019): Publicação Contínua; e37382
Acta Scientiarum. Technology; v. 41 (2019): Publicação Contínua; e37382
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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