Non-invasive quantification of vitamin C, citric acid, and sugar in ‘Valência’ oranges using infrared spectroscopies

Detalhes bibliográficos
Autor(a) principal: Borba, Karla Rodrigues [UNESP]
Data de Publicação: 2020
Outros Autores: Spricigo, Poliana Cristina, Aykas, Didem Peren, Mitsuyuki, Milene Corso, Colnago, Luiz Alberto, Ferreira, Marcos David
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1007/s13197-020-04589-x
http://hdl.handle.net/11449/200635
Resumo: Near (NIR) and mid (MIR) infrared spectroscopies have been studied as potential methods for non-destructive analyses of the fresh fruits quality. In this study, vitamin C, citric acid, total and reducing sugar content in ‘Valência’ oranges were evaluated using NIR and MIR spectroscopy with multivariate analysis. The spectral data were used to build up prediction models based on PLS (Partial Least Squares) regression. For vitamin C and citric acid, both NIR (r = 0.72 and 0.77, respectively) and MIR (0.81 and 0.91, respectively) resulted in feasible models. For sugars determination the two techniques presented a strong correlation between the reference values and analytical signals, with low RMSEP and r > 0.70 (NIR: sucrose RMSEP = 12.2 and r = 0.75; glucose RMSEP = 6.77 and r = 0.82; fructose RMSEP = 5.07 and r = 0.81; total sugar RMSEP = 12.1 and r = 0.80; reducing sugar RMSEP = 20.32 and r = 0.82; MIR: sucrose RMSEP = 9.47 and r = 0.80; glucose RMSEP = 6.70 and r = 0.82; fructose RMSEP = 5.20 and r = 0.81; total sugar RMSEP = 11.72 and r = 0.81; reducing sugar RMSEP = 20.42 and r = 0.81). The models developed with MIR presented lower prediction error rates than those made with NIR. Therefore, infrared techniques show applicability to determine of orange quality parameters in a non-destructive way.
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spelling Non-invasive quantification of vitamin C, citric acid, and sugar in ‘Valência’ oranges using infrared spectroscopiesChemometricsIntact fruit qualityMIRNIRNon-destructive analysesOrangesPLSNear (NIR) and mid (MIR) infrared spectroscopies have been studied as potential methods for non-destructive analyses of the fresh fruits quality. In this study, vitamin C, citric acid, total and reducing sugar content in ‘Valência’ oranges were evaluated using NIR and MIR spectroscopy with multivariate analysis. The spectral data were used to build up prediction models based on PLS (Partial Least Squares) regression. For vitamin C and citric acid, both NIR (r = 0.72 and 0.77, respectively) and MIR (0.81 and 0.91, respectively) resulted in feasible models. For sugars determination the two techniques presented a strong correlation between the reference values and analytical signals, with low RMSEP and r > 0.70 (NIR: sucrose RMSEP = 12.2 and r = 0.75; glucose RMSEP = 6.77 and r = 0.82; fructose RMSEP = 5.07 and r = 0.81; total sugar RMSEP = 12.1 and r = 0.80; reducing sugar RMSEP = 20.32 and r = 0.82; MIR: sucrose RMSEP = 9.47 and r = 0.80; glucose RMSEP = 6.70 and r = 0.82; fructose RMSEP = 5.20 and r = 0.81; total sugar RMSEP = 11.72 and r = 0.81; reducing sugar RMSEP = 20.42 and r = 0.81). The models developed with MIR presented lower prediction error rates than those made with NIR. Therefore, infrared techniques show applicability to determine of orange quality parameters in a non-destructive way.Department of Food and Nutrition School of Pharmaceutical Sciences São Paulo State University-UNESP, Araraquara–Jaú, Km 1Department of Crop Science University of São Paulo/ESALQ, Pádua Dias, 11Department of Food Science and Technology The Ohio State University, 100 Parker Food Science and Technology Building, 2015 Fyffe RoadDepartment of Food Engineering Faculty of Engineering Adnan Menderes UniversityEmbrapa Instrumentation, XV de Novembro, 1452Department of Food and Nutrition School of Pharmaceutical Sciences São Paulo State University-UNESP, Araraquara–Jaú, Km 1Universidade Estadual Paulista (Unesp)Universidade de São Paulo (USP)The Ohio State UniversityAdnan Menderes UniversityEmpresa Brasileira de Pesquisa Agropecuária (EMBRAPA)Borba, Karla Rodrigues [UNESP]Spricigo, Poliana CristinaAykas, Didem PerenMitsuyuki, Milene CorsoColnago, Luiz AlbertoFerreira, Marcos David2020-12-12T02:11:58Z2020-12-12T02:11:58Z2020-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1007/s13197-020-04589-xJournal of Food Science and Technology.0975-84020022-1155http://hdl.handle.net/11449/20063510.1007/s13197-020-04589-x2-s2.0-85086880610Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal of Food Science and Technologyinfo:eu-repo/semantics/openAccess2024-06-21T12:47:12Zoai:repositorio.unesp.br:11449/200635Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T22:32:50.924723Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Non-invasive quantification of vitamin C, citric acid, and sugar in ‘Valência’ oranges using infrared spectroscopies
title Non-invasive quantification of vitamin C, citric acid, and sugar in ‘Valência’ oranges using infrared spectroscopies
spellingShingle Non-invasive quantification of vitamin C, citric acid, and sugar in ‘Valência’ oranges using infrared spectroscopies
Borba, Karla Rodrigues [UNESP]
Chemometrics
Intact fruit quality
MIR
NIR
Non-destructive analyses
Oranges
PLS
title_short Non-invasive quantification of vitamin C, citric acid, and sugar in ‘Valência’ oranges using infrared spectroscopies
title_full Non-invasive quantification of vitamin C, citric acid, and sugar in ‘Valência’ oranges using infrared spectroscopies
title_fullStr Non-invasive quantification of vitamin C, citric acid, and sugar in ‘Valência’ oranges using infrared spectroscopies
title_full_unstemmed Non-invasive quantification of vitamin C, citric acid, and sugar in ‘Valência’ oranges using infrared spectroscopies
title_sort Non-invasive quantification of vitamin C, citric acid, and sugar in ‘Valência’ oranges using infrared spectroscopies
author Borba, Karla Rodrigues [UNESP]
author_facet Borba, Karla Rodrigues [UNESP]
Spricigo, Poliana Cristina
Aykas, Didem Peren
Mitsuyuki, Milene Corso
Colnago, Luiz Alberto
Ferreira, Marcos David
author_role author
author2 Spricigo, Poliana Cristina
Aykas, Didem Peren
Mitsuyuki, Milene Corso
Colnago, Luiz Alberto
Ferreira, Marcos David
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Universidade de São Paulo (USP)
The Ohio State University
Adnan Menderes University
Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA)
dc.contributor.author.fl_str_mv Borba, Karla Rodrigues [UNESP]
Spricigo, Poliana Cristina
Aykas, Didem Peren
Mitsuyuki, Milene Corso
Colnago, Luiz Alberto
Ferreira, Marcos David
dc.subject.por.fl_str_mv Chemometrics
Intact fruit quality
MIR
NIR
Non-destructive analyses
Oranges
PLS
topic Chemometrics
Intact fruit quality
MIR
NIR
Non-destructive analyses
Oranges
PLS
description Near (NIR) and mid (MIR) infrared spectroscopies have been studied as potential methods for non-destructive analyses of the fresh fruits quality. In this study, vitamin C, citric acid, total and reducing sugar content in ‘Valência’ oranges were evaluated using NIR and MIR spectroscopy with multivariate analysis. The spectral data were used to build up prediction models based on PLS (Partial Least Squares) regression. For vitamin C and citric acid, both NIR (r = 0.72 and 0.77, respectively) and MIR (0.81 and 0.91, respectively) resulted in feasible models. For sugars determination the two techniques presented a strong correlation between the reference values and analytical signals, with low RMSEP and r > 0.70 (NIR: sucrose RMSEP = 12.2 and r = 0.75; glucose RMSEP = 6.77 and r = 0.82; fructose RMSEP = 5.07 and r = 0.81; total sugar RMSEP = 12.1 and r = 0.80; reducing sugar RMSEP = 20.32 and r = 0.82; MIR: sucrose RMSEP = 9.47 and r = 0.80; glucose RMSEP = 6.70 and r = 0.82; fructose RMSEP = 5.20 and r = 0.81; total sugar RMSEP = 11.72 and r = 0.81; reducing sugar RMSEP = 20.42 and r = 0.81). The models developed with MIR presented lower prediction error rates than those made with NIR. Therefore, infrared techniques show applicability to determine of orange quality parameters in a non-destructive way.
publishDate 2020
dc.date.none.fl_str_mv 2020-12-12T02:11:58Z
2020-12-12T02:11:58Z
2020-01-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1007/s13197-020-04589-x
Journal of Food Science and Technology.
0975-8402
0022-1155
http://hdl.handle.net/11449/200635
10.1007/s13197-020-04589-x
2-s2.0-85086880610
url http://dx.doi.org/10.1007/s13197-020-04589-x
http://hdl.handle.net/11449/200635
identifier_str_mv Journal of Food Science and Technology.
0975-8402
0022-1155
10.1007/s13197-020-04589-x
2-s2.0-85086880610
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Journal of Food Science and Technology
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
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