| |
|
|
|
Registro Completo |
|
Biblioteca(s): |
Embrapa Uva e Vinho. |
|
Data corrente: |
15/10/2021 |
|
Data da última atualização: |
15/10/2021 |
|
Tipo da produção científica: |
Artigo em Periódico Indexado |
|
Autoria: |
LIMA, M. dos S.; PEREIRA, G. E.; FEDRIGO, I. M. T. |
|
Afiliação: |
MARCOS DOS SANTOS LIMA, Department of Food Technology, Federal Institute of Sertão Pernambucano, Campus Petrolina, BR 407 km 08 RdJardim São Paulo, Petrolina, PE 56314-522, Brazil; GIULIANO ELIAS PEREIRA, CNPUV; ISABELA MAIA TOALDO FEDRIGO, Department of Food Science and Technology, Federal University of Santa Catarina, Admar Gonzaga Rd., 1346, Itacorubi, Florianópolis, SC 88034-001, Brazil. |
|
Título: |
Artifcial neural network: a powerful tool in associating phenolic compounds with antioxidant activity of grape juices. |
|
Ano de publicação: |
2021 |
|
Fonte/Imprenta: |
Food Analytical Methods, 14 oct. 2021. Online. |
|
DOI: |
10.1007/s12161-021-02144-8 |
|
Idioma: |
Inglês |
|
Conteúdo: |
In vitro techniques are essential to assess the antioxidant potential of foods, although methods with diferent action mechanisms make troublesome data analysis. This article describes the use of artifcial neural network (ANN) to associate phenolic compounds with antioxidant activity in vitro (AOX) of grape juices. A multilayer perceptron (MLP) ANN was obtained with 28 phenolics quantifed, as input layers, and AOX measuring by DPPH, ABTS, FRAP, H2O2, and β-carotene/linoleic acid bleaching assay (βCLA) methods, as output layers. To improve discussion in food sciences, the ANN results were compared with Pearson?s correlation and principal component analysis (PCA), methods largely used in food studies. Pearson?s technique showed correlations between antioxidant methods and some of the phenolic compounds, but with limitations. PCA proved to be a more powerful method than Pearson?s correlation, as it positively associated 13 phenolics with four out of fve antioxidant methods. The MLP-ANN allowed simultaneous association of 19 individual phenolics, while a single hidden layer predicted 15 phenolics with simultaneous action in all AOX methods. The power of association was: ANN>PCA>Pearson. It was evidenced that ANN is a powerful tool for screening antioxidants in diferent AOX systems, which is applicable in health interests. |
|
Palavras-Chave: |
Antioxidant methods; Bioactivity; Grape polyphenol. |
|
Thesaurus Nal: |
Chemometrics. |
|
Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
|
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/226970/1/SantosLima2021-Article-ArtificialNeuralNetworkAPowerf.pdf
|
|
Marc: |
LEADER 02004naa a2200205 a 4500
001 2135356
005 2021-10-15
008 2021 bl uuuu u00u1 u #d
024 7 $a10.1007/s12161-021-02144-8$2DOI
100 1 $aLIMA, M. dos S.
245 $aArtifcial neural network$ba powerful tool in associating phenolic compounds with antioxidant activity of grape juices.$h[electronic resource]
260 $c2021
520 $aIn vitro techniques are essential to assess the antioxidant potential of foods, although methods with diferent action mechanisms make troublesome data analysis. This article describes the use of artifcial neural network (ANN) to associate phenolic compounds with antioxidant activity in vitro (AOX) of grape juices. A multilayer perceptron (MLP) ANN was obtained with 28 phenolics quantifed, as input layers, and AOX measuring by DPPH, ABTS, FRAP, H2O2, and β-carotene/linoleic acid bleaching assay (βCLA) methods, as output layers. To improve discussion in food sciences, the ANN results were compared with Pearson?s correlation and principal component analysis (PCA), methods largely used in food studies. Pearson?s technique showed correlations between antioxidant methods and some of the phenolic compounds, but with limitations. PCA proved to be a more powerful method than Pearson?s correlation, as it positively associated 13 phenolics with four out of fve antioxidant methods. The MLP-ANN allowed simultaneous association of 19 individual phenolics, while a single hidden layer predicted 15 phenolics with simultaneous action in all AOX methods. The power of association was: ANN>PCA>Pearson. It was evidenced that ANN is a powerful tool for screening antioxidants in diferent AOX systems, which is applicable in health interests.
650 $aChemometrics
653 $aAntioxidant methods
653 $aBioactivity
653 $aGrape polyphenol
700 1 $aPEREIRA, G. E.
700 1 $aFEDRIGO, I. M. T.
773 $tFood Analytical Methods, 14 oct. 2021. Online.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Uva e Vinho (CNPUV) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
|
|
|
Registro Completo
|
Biblioteca(s): |
Embrapa Acre. |
|
Data corrente: |
11/04/2018 |
|
Data da última atualização: |
16/11/2023 |
|
Tipo da produção científica: |
Resumo em Anais de Congresso |
|
Autoria: |
MOREIRA, G. T. S.; GONCALVES, R. C.; SANDRA, Y. de O.; MACEDO, P. E. F. de. |
|
Afiliação: |
Giovanna Teixeira Sandoval Moreira; RIVADALVE COELHO GONCALVES, CPAF-Acre; Yuriane de Oliveira Sandra, Universidade Federal do Acre (Ufac); PAULO EDUARDO FRANCA DE MACEDO, CPAF-Acre. |
|
Título: |
Fungos em mudas de seringueira do tipo toco enxertado de raiz nua e toco enxertado de raiz nua transplantada para recipiente, no Acre, Brasil. |
|
Ano de publicação: |
2018 |
|
Fonte/Imprenta: |
In: SEMINÁRIO DE INICIAÇÃO CIENTÍFICA DA UFAC, 26., 2017, Rio Branco. Anais... Rio Branco: Ufac, 2018. |
|
Páginas: |
p. 578. |
|
ISBN: |
978-85-8236-078-1 |
|
Idioma: |
Português |
|
Conteúdo: |
O programa estatal de fomento florestal com Hevea brasiliensis já possibilitou o plantio de aproximadamente 5000 ha desde 2012 no Acre. Um dos problemas detectados neste programa foi o alto índice de mortalidade de mudas de seringueira. Com o objetivo de estudar a causa da morte de mudas, foi realizado este estudo. |
|
Palavras-Chave: |
Acre; Amazonia Occidental; Amazônia Ocidental; Árbol de goma; Enfermedades fungales de las plantas; Hongos patógenos de las plantas; Injerto (plantas); Mortalidad; Producción de plántulas; Rio Branco (AC); Ruber tree; Senador Guiomard (AC); Western Amazon. |
|
Thesagro: |
Doença fúngica; Enxerto; Hevea brasiliensis; Mortalidade; Muda; Seringueira. |
|
Thesaurus NAL: |
Fungal diseases of plants; Grafting (plants); Mortality; Plant pathogenic fungi; Seedling production. |
|
Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
|
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/175280/1/26585.pdf
|
|
Marc: |
LEADER 01758nam a2200457 a 4500
001 2090450
005 2023-11-16
008 2018 bl uuuu u00u1 u #d
020 $a978-85-8236-078-1
100 1 $aMOREIRA, G. T. S.
245 $aFungos em mudas de seringueira do tipo toco enxertado de raiz nua e toco enxertado de raiz nua transplantada para recipiente, no Acre, Brasil.$h[electronic resource]
260 $aIn: SEMINÁRIO DE INICIAÇÃO CIENTÍFICA DA UFAC, 26., 2017, Rio Branco. Anais... Rio Branco: Ufac$c2018
300 $ap. 578.
520 $aO programa estatal de fomento florestal com Hevea brasiliensis já possibilitou o plantio de aproximadamente 5000 ha desde 2012 no Acre. Um dos problemas detectados neste programa foi o alto índice de mortalidade de mudas de seringueira. Com o objetivo de estudar a causa da morte de mudas, foi realizado este estudo.
650 $aFungal diseases of plants
650 $aGrafting (plants)
650 $aMortality
650 $aPlant pathogenic fungi
650 $aSeedling production
650 $aDoença fúngica
650 $aEnxerto
650 $aHevea brasiliensis
650 $aMortalidade
650 $aMuda
650 $aSeringueira
653 $aAcre
653 $aAmazonia Occidental
653 $aAmazônia Ocidental
653 $aÁrbol de goma
653 $aEnfermedades fungales de las plantas
653 $aHongos patógenos de las plantas
653 $aInjerto (plantas)
653 $aMortalidad
653 $aProducción de plántulas
653 $aRio Branco (AC)
653 $aRuber tree
653 $aSenador Guiomard (AC)
653 $aWestern Amazon
700 1 $aGONCALVES, R. C.
700 1 $aSANDRA, Y. de O.
700 1 $aMACEDO, P. E. F. de
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Acre (CPAF-AC) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
| Expressão de busca inválida. Verifique!!! |
|
|
