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Registro Completo |
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Biblioteca(s): |
Embrapa Amazônia Oriental. |
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Data corrente: |
04/08/2017 |
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Data da última atualização: |
28/11/2018 |
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Tipo da produção científica: |
Capítulo em Livro Técnico-Científico |
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Autoria: |
SCHWARTZ, G.; LOPES, J. do C. A. |
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Afiliação: |
GUSTAVO SCHWARTZ, CPATU; JOSE DO CARMO ALVES LOPES, CPATU. |
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Título: |
Florestas secundárias: manejo, distúrbios e sistemas agroflorestais. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
In: CORDEIRO, I. M. C. C.; RANGEL-VASCONCELOS, L. G. T.; SCHWARTZ, G.; OLIVEIRA, F. de A. (Org.). Nordeste Paraense: panorama geral e uso sustentável das florestas secundárias. Belém, PA: EDUFRA, 2017. |
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Páginas: |
Cap. 9, p. 255-276. |
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Idioma: |
Português |
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Palavras-Chave: |
Sistema agroflorestal. |
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Thesagro: |
Floresta Secundaria; Manejo. |
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Categoria do assunto: |
K Ciência Florestal e Produtos de Origem Vegetal |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/162433/1/Livro-Nordeste-6.pdf
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Marc: |
LEADER 00671naa a2200169 a 4500
001 2073640
005 2018-11-28
008 2017 bl uuuu u00u1 u #d
100 1 $aSCHWARTZ, G.
245 $aFlorestas secundárias$bmanejo, distúrbios e sistemas agroflorestais.$h[electronic resource]
260 $c2017
300 $aCap. 9, p. 255-276.
650 $aFloresta Secundaria
650 $aManejo
653 $aSistema agroflorestal
700 1 $aLOPES, J. do C. A.
773 $tIn: CORDEIRO, I. M. C. C.; RANGEL-VASCONCELOS, L. G. T.; SCHWARTZ, G.; OLIVEIRA, F. de A. (Org.). Nordeste Paraense: panorama geral e uso sustentável das florestas secundárias. Belém, PA: EDUFRA, 2017.
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Registro original: |
Embrapa Amazônia Oriental (CPATU) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Semiárido. Para informações adicionais entre em contato com cpatsa.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Semiárido. |
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Data corrente: |
18/01/2017 |
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Data da última atualização: |
17/01/2018 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
MALEGORI, C.; MARQUES, E. J. N.; FREITAS, S. T. de; PIMENTEL, M. F.; PASQUINI, C.; CASIRAGHI, E. |
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Afiliação: |
CRISTINA MALEGORI, DeFENS Department of Food, Environmental and Nutritional Sciences, Università degli Studi di Milano, Milano, Italy; EMANUEL JOSÉ NASCIMENTO MARQUES, UFPE; SERGIO TONETTO DE FREITAS, CPATSA; MARIA FERNANDA PIMENTEL, UFPE; CELIO PASQUINI, Institute of Chemistry, University of Campinas, Campinas (SP); ERNESTINA CASIRAGHI, DeFENS Department of Food, Environmental and Nutritional Sciences, Università degli Studi di Milano, Milano, Italy. |
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Título: |
Comparing the analytical performances of Micro-NIR and FT-NIR spectrometers in the evaluation of acerola fruit quality, using PLS and SVM regression algorithms. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
Talanta, v. 165, 112-116, 2017. |
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DOI: |
10.1016/j.talanta.2016.12.035 |
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Idioma: |
Inglês |
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Conteúdo: |
The main goal of this study was to investigate the analytical performances of a state-of-the-art device, one of the smallest dispersion NIR spectrometers on the market (MicroNIR 1700), making a critical comparison with a benchtop FT-NIR spectrometer in the evaluation of the prediction accuracy. In particular, the aim of this study was to estimate in a non-destructive manner, titratable acidity and ascorbic acid content in acerola fruit during ripening, in a view of direct applicability in field of this new miniaturised handheld device. Acerola (Malpighia emarginata DC.) is a super-fruit characterised by a considerable amount of ascorbic acid, ranging from 1.0% to 4.5%. However, during ripening, acerola colour changes and the fruit may lose as much as half of its ascorbic acid content. Because the variability of chemical parameters followed a non-strictly linear profile, two different regression algorithms were compared: PLS and SVM. Regression models obtained with Micro-NIR spectra give better results using SVM algorithm, for both ascorbic acid and titratable acidity estimation. FT-NIR data give comparable results using both SVM and PLS algorithms, with lower errors for SVM regression. The prediction ability of the two instruments was statistically compared using the Passing-Bablok regression algorithm; the outcomes are critically discussed together with the regression models, showing the suitability of the portable Micro-NIR for in field monitoring of chemical parameters of interest in acerola fruits. MenosThe main goal of this study was to investigate the analytical performances of a state-of-the-art device, one of the smallest dispersion NIR spectrometers on the market (MicroNIR 1700), making a critical comparison with a benchtop FT-NIR spectrometer in the evaluation of the prediction accuracy. In particular, the aim of this study was to estimate in a non-destructive manner, titratable acidity and ascorbic acid content in acerola fruit during ripening, in a view of direct applicability in field of this new miniaturised handheld device. Acerola (Malpighia emarginata DC.) is a super-fruit characterised by a considerable amount of ascorbic acid, ranging from 1.0% to 4.5%. However, during ripening, acerola colour changes and the fruit may lose as much as half of its ascorbic acid content. Because the variability of chemical parameters followed a non-strictly linear profile, two different regression algorithms were compared: PLS and SVM. Regression models obtained with Micro-NIR spectra give better results using SVM algorithm, for both ascorbic acid and titratable acidity estimation. FT-NIR data give comparable results using both SVM and PLS algorithms, with lower errors for SVM regression. The prediction ability of the two instruments was statistically compared using the Passing-Bablok regression algorithm; the outcomes are critically discussed together with the regression models, showing the suitability of the portable Micro-NIR for in field monitoring of chemical parameters of... Mostrar Tudo |
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Palavras-Chave: |
Máquinas vector de suporte; MicroNIR; Partial Least Squares (PLS); Passing-Bablok regre; Regressão de Passo-Bablok; Support Vector Machines (SVM). |
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Thesagro: |
Acerola; Acidez; Maturação; Vitamina C. |
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Thesaurus NAL: |
Malpighia emarginata. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 02552naa a2200325 a 4500
001 2061108
005 2018-01-17
008 2017 bl uuuu u00u1 u #d
024 7 $a10.1016/j.talanta.2016.12.035$2DOI
100 1 $aMALEGORI, C.
245 $aComparing the analytical performances of Micro-NIR and FT-NIR spectrometers in the evaluation of acerola fruit quality, using PLS and SVM regression algorithms.$h[electronic resource]
260 $c2017
520 $aThe main goal of this study was to investigate the analytical performances of a state-of-the-art device, one of the smallest dispersion NIR spectrometers on the market (MicroNIR 1700), making a critical comparison with a benchtop FT-NIR spectrometer in the evaluation of the prediction accuracy. In particular, the aim of this study was to estimate in a non-destructive manner, titratable acidity and ascorbic acid content in acerola fruit during ripening, in a view of direct applicability in field of this new miniaturised handheld device. Acerola (Malpighia emarginata DC.) is a super-fruit characterised by a considerable amount of ascorbic acid, ranging from 1.0% to 4.5%. However, during ripening, acerola colour changes and the fruit may lose as much as half of its ascorbic acid content. Because the variability of chemical parameters followed a non-strictly linear profile, two different regression algorithms were compared: PLS and SVM. Regression models obtained with Micro-NIR spectra give better results using SVM algorithm, for both ascorbic acid and titratable acidity estimation. FT-NIR data give comparable results using both SVM and PLS algorithms, with lower errors for SVM regression. The prediction ability of the two instruments was statistically compared using the Passing-Bablok regression algorithm; the outcomes are critically discussed together with the regression models, showing the suitability of the portable Micro-NIR for in field monitoring of chemical parameters of interest in acerola fruits.
650 $aMalpighia emarginata
650 $aAcerola
650 $aAcidez
650 $aMaturação
650 $aVitamina C
653 $aMáquinas vector de suporte
653 $aMicroNIR
653 $aPartial Least Squares (PLS)
653 $aPassing-Bablok regre
653 $aRegressão de Passo-Bablok
653 $aSupport Vector Machines (SVM)
700 1 $aMARQUES, E. J. N.
700 1 $aFREITAS, S. T. de
700 1 $aPIMENTEL, M. F.
700 1 $aPASQUINI, C.
700 1 $aCASIRAGHI, E.
773 $tTalanta$gv. 165, 112-116, 2017.
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