Non-destructive determination of color, titratable acidity, and dry matter in intact tomatoes using a portable Vis-NIR spectrometer
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/j.jfca.2021.104288 http://hdl.handle.net/11449/223058 |
Resumo: | Fruit color and chemical composition, particularly dry matter and titratable acidity (TA), are important tomato-quality parameters for consumers. Therefore, a single test allowing for the evaluation of these parameters simultaneously would improve the efficiency of this analysis. Vis-NIR spectroscopy has been used to identify many compounds in fruits and vegetables, therefore, here, a portable Vis-NIR spectrometer was used to collect the spectra of fresh tomatoes produced from November 2018 to November 2019, in five tomato cropping regions in Brazil, namely, Goiás, Bahia, Santa Catarina, Minas Gerais, and São Paulo states. Calibration and prediction models were developed using the 396–1,131 nm spectral region, through principal component analysis (PCA), and partial least square regression (PLS). Strong prediction results (root mean square of error prediction, RMSEP; coefficient of prediction, Rp²; and standard deviation ratio, SDR) were obtained for the color parameter a*, representing red (RMSEP = 2.89, Rp² = 0.94, SDR = 4.11), and the amount of dry matter (RMSEP = 0.46 %; Rp² = 0.59 % SDR = 1.92). However, poor prediction results were obtained for titratable acidity (RMSEP = 0.07 %; SDR = 1.15). These findings indicate that color (a*) and dry matter of intact tomatoes may be predicted using a portable Vis-NIR spectrometer. |
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Non-destructive determination of color, titratable acidity, and dry matter in intact tomatoes using a portable Vis-NIR spectrometerChemometricsPartial least squarePortable Vis-NirPrincipal component analysisQuality foodFruit color and chemical composition, particularly dry matter and titratable acidity (TA), are important tomato-quality parameters for consumers. Therefore, a single test allowing for the evaluation of these parameters simultaneously would improve the efficiency of this analysis. Vis-NIR spectroscopy has been used to identify many compounds in fruits and vegetables, therefore, here, a portable Vis-NIR spectrometer was used to collect the spectra of fresh tomatoes produced from November 2018 to November 2019, in five tomato cropping regions in Brazil, namely, Goiás, Bahia, Santa Catarina, Minas Gerais, and São Paulo states. Calibration and prediction models were developed using the 396–1,131 nm spectral region, through principal component analysis (PCA), and partial least square regression (PLS). Strong prediction results (root mean square of error prediction, RMSEP; coefficient of prediction, Rp²; and standard deviation ratio, SDR) were obtained for the color parameter a*, representing red (RMSEP = 2.89, Rp² = 0.94, SDR = 4.11), and the amount of dry matter (RMSEP = 0.46 %; Rp² = 0.59 % SDR = 1.92). However, poor prediction results were obtained for titratable acidity (RMSEP = 0.07 %; SDR = 1.15). These findings indicate that color (a*) and dry matter of intact tomatoes may be predicted using a portable Vis-NIR spectrometer.Ministério da Ciência, Tecnologia, Inovações e ComunicaçõesUniversidade Federal de Goiás Escola de Agronomia Programa de Pós-Graduação em Agronomia Universidade Federal de Goiás Rodovia Goiânia-Nova Veneza, Km 0 s/n Campus - SamambaiaUniversidade Federal de Goiás Escola de Agronomia Universidade Federal de Goiás Rodovia Goiânia-Nova Veneza, Km 0 s/n Campus - SamambaiaUniversidade Federal de Goiás Escola de Agronomia Departamento de Horticultura Universidade Federal de Goiás Rodovia Goiânia-Nova Veneza, Km 0 s/n Campus - SamambaiaUniversidade Federal de Goiás Escola de Agronomia Departamento de Engenharia de Alimentos Universidade Federal de Goiás Rodovia Goiânia-Nova Veneza, Km 0 s/n Campus - SamambaiaUniversidade Estadual Paulista (UNESP) Faculdade de Ciências Agrárias e Veterinárias (FCAV), Campus de Jaboticabal, Via de Acesso Prof. Paulo Donato Castellane s/n. JaboticabalUniversidade Estadual Paulista (UNESP) Faculdade de Ciências Agrárias e Veterinárias (FCAV), Campus de Jaboticabal, Via de Acesso Prof. Paulo Donato Castellane s/n. JaboticabalUniversidade Federal de Goiás (UFG)Universidade Estadual Paulista (UNESP)Arruda de Brito, AnnelisaCampos, Fernandados Reis Nascimento, AbadiaDamiani, ClarissaAlves da Silva, Fláviode Almeida Teixeira, Gustavo Henrique [UNESP]Cunha Júnior, Luis Carlos2022-04-28T19:48:22Z2022-04-28T19:48:22Z2022-04-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1016/j.jfca.2021.104288Journal of Food Composition and Analysis, v. 107.0889-1575http://hdl.handle.net/11449/22305810.1016/j.jfca.2021.1042882-s2.0-85121215021Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal of Food Composition and Analysisinfo:eu-repo/semantics/openAccess2022-04-28T19:48:22Zoai:repositorio.unesp.br:11449/223058Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:13:02.635687Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Non-destructive determination of color, titratable acidity, and dry matter in intact tomatoes using a portable Vis-NIR spectrometer |
title |
Non-destructive determination of color, titratable acidity, and dry matter in intact tomatoes using a portable Vis-NIR spectrometer |
spellingShingle |
Non-destructive determination of color, titratable acidity, and dry matter in intact tomatoes using a portable Vis-NIR spectrometer Arruda de Brito, Annelisa Chemometrics Partial least square Portable Vis-Nir Principal component analysis Quality food |
title_short |
Non-destructive determination of color, titratable acidity, and dry matter in intact tomatoes using a portable Vis-NIR spectrometer |
title_full |
Non-destructive determination of color, titratable acidity, and dry matter in intact tomatoes using a portable Vis-NIR spectrometer |
title_fullStr |
Non-destructive determination of color, titratable acidity, and dry matter in intact tomatoes using a portable Vis-NIR spectrometer |
title_full_unstemmed |
Non-destructive determination of color, titratable acidity, and dry matter in intact tomatoes using a portable Vis-NIR spectrometer |
title_sort |
Non-destructive determination of color, titratable acidity, and dry matter in intact tomatoes using a portable Vis-NIR spectrometer |
author |
Arruda de Brito, Annelisa |
author_facet |
Arruda de Brito, Annelisa Campos, Fernanda dos Reis Nascimento, Abadia Damiani, Clarissa Alves da Silva, Flávio de Almeida Teixeira, Gustavo Henrique [UNESP] Cunha Júnior, Luis Carlos |
author_role |
author |
author2 |
Campos, Fernanda dos Reis Nascimento, Abadia Damiani, Clarissa Alves da Silva, Flávio de Almeida Teixeira, Gustavo Henrique [UNESP] Cunha Júnior, Luis Carlos |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Federal de Goiás (UFG) Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Arruda de Brito, Annelisa Campos, Fernanda dos Reis Nascimento, Abadia Damiani, Clarissa Alves da Silva, Flávio de Almeida Teixeira, Gustavo Henrique [UNESP] Cunha Júnior, Luis Carlos |
dc.subject.por.fl_str_mv |
Chemometrics Partial least square Portable Vis-Nir Principal component analysis Quality food |
topic |
Chemometrics Partial least square Portable Vis-Nir Principal component analysis Quality food |
description |
Fruit color and chemical composition, particularly dry matter and titratable acidity (TA), are important tomato-quality parameters for consumers. Therefore, a single test allowing for the evaluation of these parameters simultaneously would improve the efficiency of this analysis. Vis-NIR spectroscopy has been used to identify many compounds in fruits and vegetables, therefore, here, a portable Vis-NIR spectrometer was used to collect the spectra of fresh tomatoes produced from November 2018 to November 2019, in five tomato cropping regions in Brazil, namely, Goiás, Bahia, Santa Catarina, Minas Gerais, and São Paulo states. Calibration and prediction models were developed using the 396–1,131 nm spectral region, through principal component analysis (PCA), and partial least square regression (PLS). Strong prediction results (root mean square of error prediction, RMSEP; coefficient of prediction, Rp²; and standard deviation ratio, SDR) were obtained for the color parameter a*, representing red (RMSEP = 2.89, Rp² = 0.94, SDR = 4.11), and the amount of dry matter (RMSEP = 0.46 %; Rp² = 0.59 % SDR = 1.92). However, poor prediction results were obtained for titratable acidity (RMSEP = 0.07 %; SDR = 1.15). These findings indicate that color (a*) and dry matter of intact tomatoes may be predicted using a portable Vis-NIR spectrometer. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-04-28T19:48:22Z 2022-04-28T19:48:22Z 2022-04-01 |
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/10.1016/j.jfca.2021.104288 Journal of Food Composition and Analysis, v. 107. 0889-1575 http://hdl.handle.net/11449/223058 10.1016/j.jfca.2021.104288 2-s2.0-85121215021 |
url |
http://dx.doi.org/10.1016/j.jfca.2021.104288 http://hdl.handle.net/11449/223058 |
identifier_str_mv |
Journal of Food Composition and Analysis, v. 107. 0889-1575 10.1016/j.jfca.2021.104288 2-s2.0-85121215021 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Journal of Food Composition and Analysis |
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 |
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_version_ |
1808128774371278848 |