| Registro completo |
| Provedor de dados: |
CIGR Journal
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| País: |
China
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| Título: |
Optimization of Bioactive Compound’s Extraction Conditions from Beetroot by Means of Artificial Neural Networks (ANN)
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| Autores: |
Guiné, Raquel P.F.
Mendes, Mateus
Gonçalves, Fernando
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| Data: |
2019-12-16
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| Ano: |
2019
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| Palavras-chave: |
Food Science
Food Chemistry Phenolic compounds
Antioxidant activity
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| Resumo: |
The present work used Artificial Neural Network (ANN) models to correlate beetroot extraction conditions with total phenolic compounds (TPC), anthocyanins (ANT) and antioxidant activity (AOA). The input variables were extraction time, type of solvent, solvent volume/sample mass (VMR) and order of extraction. The ANN models produced showed very good accuracy (R > 94 %), being suitable for data mining using weight analysis techniques. The experiments involved variable conditions: solvents (Methanol, ethanol:water and acetone:water), extraction times (15 and 60 min), VMR (5, 10 and 20), order of extract (3 sequential extractions). The TPC were evaluated by the Folin-Ciocalteu method, ANT by the SO2 bleaching method and AOA following the ABTS method. The experimental results showed that the extracting solutions used in this study exhibited similar extraction efficiency for TPC, but not for AOA. Also, the results allowed concluding that a higher VMR originated extracts with higher amounts of TPC and AOA.
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| Tipo: |
Info:eu-repo/semantics/article
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| Idioma: |
Inglês
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| Identificador: |
http://www.cigrjournal.org/index.php/Ejounral/article/view/5449
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| Editor: |
International Commission of Agricultural and Biosystems Engineering
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| Relação: |
http://www.cigrjournal.org/index.php/Ejounral/article/view/5449/3213
http://www.cigrjournal.org/index.php/Ejounral/article/downloadSuppFile/5449/2432
http://www.cigrjournal.org/index.php/Ejounral/article/downloadSuppFile/5449/2433
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| Formato: |
application/pdf
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| Fonte: |
Agricultural Engineering International: CIGR Journal; Vol 21, No 4 (2019): CIGR Journal; 216-223
1682-1130
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| Direitos: |
Copyright (c) 2019 Agricultural Engineering International: CIGR Journal
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