Non-invasive quantification of vitamin C, citric acid, and sugar in ‘Valência’ oranges using infrared spectroscopies
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , |
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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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) |
repository.mail.fl_str_mv |
|
_version_ |
1808129435471183872 |