Estimating microalgae Synechococcus nidulans daily biomass concentration using neuro-fuzzy network
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| Format: | Artículo científico |
| Language: | en |
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Sociedade Brasileira de Ciência e Tecnologia de Alimentos
2013
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| author | Vitor Badiale FURLONG |
| author_facet | Vitor Badiale FURLONG |
| contents | Estimating microalgae Synechococcus nidulans daily biomass concentration using neuro-fuzzy network Vitor Badiale FURLONG Renato Dutra PEREIRA FILHO Ana Cláudia MARGARITES Pâmela Guder GOULARTE Jorge Alberto Vieira COSTA Agrociencias box Black cellular concentration predictive microbiology In this study, a neuro-fuzzy estimator was developed for the estimation of biomass concentration of the microalgae Synechococcus nidulansfrom initial batch concentrations, aiming to predict daily productivity. Nine replica experiments were performed. The growth was monitored daily through the culture medium optic density and kept constant up to the end of the exponential phase. The network training followed a full 3³ factorial design, in which the factors were the number of days in the entry vector (3,5 and 7 days), number of clusters (10, 30 and 50 clusters) and internal weight softening parameter (Sigma) (0.30, 0.45 and 0.60). These factors were confronted with the sum of the quadratic error in the validations. The validations had 24 (A) and 18 (B) days of culture growth. The validations demonstrated that in long-term experiments (Validation A) the use of a few clusters and high Sigma is necessary. However, in short-term experiments (Validation B), Sigma did not influence the result. The optimum point occurred within 3 days in the entry vector, 10 clusters and 0.60 Sigma and the mean determination coefficient was 0.95. The neuro-fuzzy estimator proved a credible alternative to predict the microalgae growth. 2013 artículo científico 0101-2061 https://www.redalyc.org/articulo.oa?id=395940119021 en http://www.redalyc.org/revista.oa?id=3959 Ciência e Tecnologia de Alimentos application/pdf Sociedade Brasileira de Ciência e Tecnologia de Alimentos Ciência e Tecnologia de Alimentos (Brasil) Num.1 Vol.33 |
| format | Artículo científico |
| id | redalyc_395940119021 |
| institution | Redalyc |
| language | en |
| publishDate | 2013 |
| publisher | Sociedade Brasileira de Ciência e Tecnologia de Alimentos |
| spellingShingle | Estimating microalgae Synechococcus nidulans daily biomass concentration using neuro-fuzzy network Vitor Badiale FURLONG Agrociencias box Black cellular concentration predictive microbiology Estimating microalgae Synechococcus nidulans daily biomass concentration using neuro-fuzzy network Vitor Badiale FURLONG Renato Dutra PEREIRA FILHO Ana Cláudia MARGARITES Pâmela Guder GOULARTE Jorge Alberto Vieira COSTA Agrociencias box Black cellular concentration predictive microbiology In this study, a neuro-fuzzy estimator was developed for the estimation of biomass concentration of the microalgae Synechococcus nidulansfrom initial batch concentrations, aiming to predict daily productivity. Nine replica experiments were performed. The growth was monitored daily through the culture medium optic density and kept constant up to the end of the exponential phase. The network training followed a full 3³ factorial design, in which the factors were the number of days in the entry vector (3,5 and 7 days), number of clusters (10, 30 and 50 clusters) and internal weight softening parameter (Sigma) (0.30, 0.45 and 0.60). These factors were confronted with the sum of the quadratic error in the validations. The validations had 24 (A) and 18 (B) days of culture growth. The validations demonstrated that in long-term experiments (Validation A) the use of a few clusters and high Sigma is necessary. However, in short-term experiments (Validation B), Sigma did not influence the result. The optimum point occurred within 3 days in the entry vector, 10 clusters and 0.60 Sigma and the mean determination coefficient was 0.95. The neuro-fuzzy estimator proved a credible alternative to predict the microalgae growth. 2013 artículo científico 0101-2061 https://www.redalyc.org/articulo.oa?id=395940119021 en http://www.redalyc.org/revista.oa?id=3959 Ciência e Tecnologia de Alimentos application/pdf Sociedade Brasileira de Ciência e Tecnologia de Alimentos Ciência e Tecnologia de Alimentos (Brasil) Num.1 Vol.33 |
| title | Estimating microalgae Synechococcus nidulans daily biomass concentration using neuro-fuzzy network |
| topic | Agrociencias box Black cellular concentration predictive microbiology |
| url | https://www.redalyc.org/articulo.oa?id=395940119021 |