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Registro Completo |
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Biblioteca(s): |
Embrapa Instrumentação. |
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Data corrente: |
27/08/2020 |
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Data da última atualização: |
16/08/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
BORBA, K. R.; SPRICIGO, P. C.; AYKAS, D. P.; FOSCHINI, M. M.; COLNAGO, L. A.; FERREIRA, M. D. |
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Afiliação: |
MILENE CORSO MITSUYUKI, CNPDIA; LUIZ ALBERTO COLNAGO, CNPDIA; MARCOS DAVID FERREIRA, CNPDIA. |
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Título: |
Non-invasive quantification of vitamin C, citric acid, and sugar in "Valência" oranges using infrared spectroscopies. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Journal of Food Science and Technology,v. 58, n. 2 2021. |
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Páginas: |
731-738 |
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ISSN: |
0022-1155 |
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DOI: |
https://doi.org/10.1007/s13197-020-04589-x |
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Idioma: |
Inglês |
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Conteúdo: |
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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Palavras-Chave: |
Intact fruit quality; MIR; NIR; Non-destructive analyses; PLS. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02242naa a2200277 a 4500
001 2124589
005 2022-08-16
008 2021 bl uuuu u00u1 u #d
022 $a0022-1155
024 7 $ahttps://doi.org/10.1007/s13197-020-04589-x$2DOI
100 1 $aBORBA, K. R.
245 $aNon-invasive quantification of vitamin C, citric acid, and sugar in "Valência" oranges using infrared spectroscopies.$h[electronic resource]
260 $c2021
300 $a731-738
520 $aNear (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.
653 $aIntact fruit quality
653 $aMIR
653 $aNIR
653 $aNon-destructive analyses
653 $aPLS
700 1 $aSPRICIGO, P. C.
700 1 $aAYKAS, D. P.
700 1 $aFOSCHINI, M. M.
700 1 $aCOLNAGO, L. A.
700 1 $aFERREIRA, M. D.
773 $tJournal of Food Science and Technology,v. 58$gn. 2 2021.
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| 1. |  | FREITAS-VANZO, A. T. de; SILVA, C. de C. da; NOVAES, T. G. de; WALZ, D. M.; MARCELINO-GUIMARÃES, F. C.; KUWAHARA, M. K.; MOLINA, R. de O.; LEITE JUNIOR, R. P. Evaluation of disease severity caused by Bean golden mosaic virus in different bean cultivars. Canadian Journal of Plant Pathology, v. 43, N. 1, p. 172-178, 2021.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: B - 1 |
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