Modeling of Biomass Production of Haematococcus pluvialis

Galvão, Rosana Machado; Santana, T. S. de; Fontes, Cristiano Hora; Sales, Emerson Andrade

doi:10.4236/am.2013.48a008

Cited by 15 publications

(11 citation statements)

References 13 publications

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“…The optimized biomass concentrations and maximum productivity for the hybrid ANN were 10% and 40%, respectively, higher than those predicted by the deterministic kinetic model [65]. Likewise, Galvão et al [94] investigated the influence of pH on biomass concentration using ANN and indicated that the neural network model was able to efficiently predict the process output. The aforementioned reports and other studies on the use of ANNs for optimization of biomass concentration for microalgae biodiesel production are summarized in Table 4.…”

Section: Microalgae Biodiesel Productionmentioning

confidence: 99%

Artificial neural networks: an efficient tool for modelling and optimization of biofuel production (a mini review)

Sewsynker-Sukai

Faloye

Kana

2016

Biotechnology & Biotechnological Equipment

118

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In view of the looming energy crisis as a result of depleting fossil fuel resources and environmental concerns from greenhouse gas emissions, the need for sustainable energy sources has secured global attention. Research is currently focused towards renewable sources of energy due to their availability and environmental friendliness. Biofuel production like other bioprocesses is controlled by several process parameters including pH, temperature and substrate concentration; however, the improvement of biofuel production requires a robust process model that accurately relates the effect of input variables to the process output. Artificial neural networks (ANNs) have emerged as a tool for modelling complex, non-linear processes. ANNs are applied in the prediction of various processes; they are useful for virtual experimentations and can potentially enhance bioprocess research and development. In this study, recent findings on the application of ANN for the modelling and optimization of biohydrogen, biogas, biodiesel, microbial fuel cell technology and bioethanol are reviewed. In addition, comparative studies on the modelling efficiency of ANN and other techniques such as the response surface methodology are briefly discussed. The review highlights the efficiency of ANNs as a modelling and optimization tool in biofuel process development.

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Section: Microalgae Biodiesel Productionmentioning

confidence: 99%

Artificial neural networks: an efficient tool for modelling and optimization of biofuel production (a mini review)

Sewsynker-Sukai

Faloye

Kana

2016

Biotechnology & Biotechnological Equipment

118

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“…Kinetic models serves in designing a bioreactor, controlling the microbial processes and predicting the behavior of the processes more easily than laboratory experiments (Bailley and Ollis 1986 ). To learn the dynamics of biomass growth and lipid production by microalgae, suitable kinetic modeling has to be developed for predicting the performance and optimization of photobioreactor operating conditions (Galvao et al 2013 ). Many research studies have been conducted and many mathematical models proposed for microalgal growth and lipid production.…”

Section: Introductionmentioning

confidence: 99%

Kinetic modeling of microalgal growth and lipid synthesis for biodiesel production

et al. 2014

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A mathematical modeling of microalgae biomass is an essential step to optimize the biomass and lipid production rate and to reduce the cost of microalgal biodiesel production system. In the present study, kinetic studies were carried out to describe the growth and neutral lipid production of two marine microalgae Chlorella salina and Nannochloropsis oculata under the nitrogen-repleted and -depleted conditions using logistic and Luedeking–Piret equations. This research paper provides the information on mathematically efficient procedure to predict suitable environment condition for biomass and lipid production. The predicted results were compared with experimental data, which showed that this model closely agreed with simulated results. From this investigation, it was found that nitrogen was an essential nutrient for algal growth, which increased under nitrogen-rich condition, whereas during nitrogen-limited condition some loss in growth was observed but with increased lipid content. Since metabolic changes occurred under nitrogen- depleted state, the protein and carbohydrate pathways were shifted to lipid biosynthesis.

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“…A influência do pH sobre o crescimento celular foi verificada no décimo dia de cultivo onde ocorreu a maior variação de pH (7,4) ocorrendo maior concentração celular (1,13 g.L -1 ). Esse comportamento é esperado, pois, de acordo com Galvão et al (2013), normalmente a microalga H. pluvialis entra em estado de excitação em pH mais baixos, passando a produzir mais pigmento. Sarada, Bhattacharya e Ravishankar (2002) relatam que, para a mesma microalga, o pH ótimo para produção de biomassa e astaxantina está na faixa de 7,0-7,8.…”

Section: Resultsunclassified

“…As microalgas, por serem fotossintéticas, absorvem e utilizam CO 2 como a principal fonte de carbono no crescimento celular. Logo, a biossíntese de carotenoides pode ocorrer pela limitação do nitrogênio em presença de excesso de fontes de carbono, como a utilização de CO 2 ou acetato e glicose em cultivos mixotróficos (GALVÃO et al, 2013).…”

Section: Introductionunclassified

Influência do CO2 no Crescimento de Haematococcus Pluvialis e na Produção de Carotenoides

Reis

Machado

Ores

et al. 2019

UNIC

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O crescimento celular da microalga de água doce Haematococcus pluvialis e a bioprodução de carotenoides são influenciados pelas diferentes condições de cultivo, como deficiência de nutrientes, iluminância, aeração, agitação, temperatura e pH, alterando sua morfologia celular e produzindo cistos avermelhados (carotenogênese). A aeração nos cultivos de microalgas está relacionada a alguns fatores que influenciam no crescimento celular. As microalgas absorvem e utilizam CO2 como a principal fonte de carbono no crescimento celular. Logo, a biossíntese de pigmentos pode ocorrer pela limitação do nitrogênio em presença de excesso de fontes de carbono. O objetivo desse trabalho foi investigar a influência do emprego de CO2 na aeração do cultivo da microalga Haematococcus pluvialis sob o crescimento celular e a bioprodução de carotenoides. No cultivo foi utilizado o meio mixotrófico BBM (Bold Basal Medium) e acetato de sódio, empregando 20% de inóculo em pH inicial de 7,0, aeração de 0,30 L.min-1, com 30% de injeção de CO2 uma vez ao dia durante 1 h, sob iluminância de 6 klux, à 25 ºC durante 22 dias. Nestas condições o crescimento celular alcançou o máximo de 1,13±0,39 g.L-1 (10 dias) e os carotenoides totais 2949,91±988,65 µg.g-1, onde foi observado que a suplementação de CO2 como fonte de carbono dissolvida no meio de cultivo pode influenciar o crescimento celular e os carotenoides totais. Palavras-chave: Microalga. Pigmento. Aeração. Cultivo. AbstractThe cellular growth of the freshwater microalgae Haematococcus pluvialis and the bioproduction of carotenoids are influenced by the different culture conditions, such as nutrient deficiency, illuminance, aeration, agitation, temperature and pH, altering its cellular morphology and producing reddish cysts (carotenogenesis). Aeration in microalgae cultures is related to some factors that influence cell growth. Microalgae absorb and utilize CO2 as the main source of carbon in cell growth. Therefore, the biosynthesis of pigments can occur by the limitation of nitrogen in the presence of excess carbon sources. The objective of this work was to investigate the influence of the use of CO2 on the aeration of the microalgae Haematococcus pluvialis under cell growth and bioproduction of carotenoids. In the culture, mixotrophic medium BBM (Bold Basal Medium) and sodium acetate were used, using 20% of inoculum at initial pH of 7.0, aeration of 0.30 L.min-1, with 30% of CO2 injection once a day for 1 h under 6 Klux illuminance at 25 ° C for 22 days. Under these conditions the cell growth reached a maximum of 1.13 ± 0.39 g. L-1 (10 days) and the total carotenoids 2949.91 ± 988.65 μg.g-1, where it was observed that CO2 supplementation as a source of carbon dissolved in the culture medium may influence cell growth and total carotenoids. Keywords: microalgae; pigment; aeration; cultivation.

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Modeling of Biomass Production of Haematococcus pluvialis

Cited by 15 publications

References 13 publications

Artificial neural networks: an efficient tool for modelling and optimization of biofuel production (a mini review)

Artificial neural networks: an efficient tool for modelling and optimization of biofuel production (a mini review)

Kinetic modeling of microalgal growth and lipid synthesis for biodiesel production

Influência do CO2 no Crescimento de Haematococcus Pluvialis e na Produção de Carotenoides

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