Application of response surface methodology (RSM) for optimizing biomass production in Nannochloropsis oculata UTEX 2164

Mehra, Anju; Jutur, Pannaga Pavan

doi:10.1007/s10811-022-02774-3

Cited by 3 publications

(2 citation statements)

References 85 publications

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“…Response surfaces method (RSM) is a useful mathematical optimization model in the analysis of multivariate quantitative processing experiments [ 14 ]. Therefore, it has been frequently performed on optimal experimental designs to optimize algal growth and pigment production [ 15 , 16 , 17 ]. Artificial Intelligence (AI) algorithms consist of several types, including boosted regression tree (BRT), artificial neural network (ANN), support vector machine (SVM) and radial basis function neural network (RBFNN), etc.…”

Section: Introductionmentioning

confidence: 99%

Response Surfaces Method and Artificial Intelligence Approaches for Modeling the Effects of Environmental Factors on Chlorophyll a in Isochrysis galbana

et al. 2023

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This study reported the condition optimization for chlorophyll a (Chl a) from the microalga Isochrysis galbana. The key parameters affecting the Chl a content of I. galbana were determined by a single-factor optimization experiment. Then the individual and interaction of three factors, including salinity, pH and nitrogen concentration, was optimized by using the method of Box–Benhnken Design. The highest Chl a content (0.51 mg/L) was obtained under the optimum conditions of salinity 30‰ and nitrogen concentration of 72.1 mg/L at pH 8.0. The estimation models of Chl a content based on the response surfaces method (RSM) and three different artificial intelligence models of artificial neural network (ANN), support vector machine (SVM) and radial basis function neural network (RBFNN), were established, respectively. The fitting model was evaluated by using statistical analysis parameters. The high accuracy of prediction was achieved on the ANN, SVM and RBFNN models with correlation coefficients (R2) of 0.9113, 0.9127, and 0.9185, respectively. The performance of these artificial intelligence models depicted better prediction capability than the RSM model for anticipating all the responses. Further experimental results suggested that the proposed SVM and RBFNN model are efficient techniques for accurately fitting the Chl a content of I. galbana and will be helpful in validating future experimental work on the Chl a content by computational intelligence approach.

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Section: Introductionmentioning

confidence: 99%

Response Surfaces Method and Artificial Intelligence Approaches for Modeling the Effects of Environmental Factors on Chlorophyll a in Isochrysis galbana

et al. 2023

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“…Most optimization studies for Nannochloropsis oculata have focused on biodiesel production [12][13][14] or the effects of nutrient ratios in the medium [15][16][17]. In this study, we decided to investigate the effects of temperature, pH and light period on the biomass composition, fatty acid profile and quality of ethanolic extracts, as a continuation of previous work for the production of antioxidants and aquaculture feed from marine microalgae [3,4].…”

Section: Introductionmentioning

confidence: 99%

Production of Antioxidants and High Value Biomass from Nannochloropsis oculata: Effects of pH, Temperature and Light Period in Batch Photobioreactors

et al. 2022

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Nannochloropsis oculata is a marine microalgal species with a great potential as food or feed due to its high pigment, protein and eicosapentaenoic acid contents. However, for such an application to be realized on a large scale, a biorefinery approach is necessary due to the high cost of microalgal biomass production. For example, techno economic analyses have suggested the co-production of food or feed with antioxidants, which can be extracted and supplied separately to the market. The aim of this study was to investigate the effect of cultivation conditions on the antioxidant capacity of Nannochlosopsis oculata extracts, derived with ultrasound-assisted extraction at room temperature, as well as the proximate composition and fatty acid profile of the biomass. A fractional factorial approach was applied to examine the effects of temperature (20–35 °C), pH (6.5–9.5) and light period (24:0, 12:12). At the end of each run, biomass was collected, washed with 0.5M ammonium bicarbonate and freeze-dried. Antioxidant capacity as gallic acid equivalents as well as pigment content were measured in the ethanolic extracts. Optimal conditions were different for productivity and biomass composition. Interesting results regarding the effect of light period (LP) and pH require further investigation, whereas the effect of moisture on the extraction process was confounded with biomass composition. Finally, further data is provided regarding the relation between chlorophyll content and apparent phenolic content using the Folin–Ciocalteu assay, in agreement with our previous work.

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Alternative culture medium for Nannochloropsis oculata mass culture

Neves,

Sales,

Ikeda

et al. 2024

Preprint

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Microalgae of the genus Nannochloropsis are highly valued in aquaculture due to their protein, fatty acid, and carotenoid content, offering potential as additives or substitutes for fish meal or oil. However, large-scale production encounters challenges, particularly concerning the culture medium. Thus, this study aimed to assess the impact of substituting artificial sea salt with common salt and standard medium with agricultural fertilizer in Nannochloropsis oculata production. Initially, the effects of reduced salinity were evaluated at salinities of 30, 10, 5, and 1 ups, followed by an examination of the effects of replacing artificial sea salt with common salt and using agricultural fertilizer on microalgae growth. Salinities of 30 and 10 exhibited the highest growth parameters. The salt source had no significant impact on culture growth, while the agricultural fertilizer enhanced it. Common salt increased the concentration of eicosapentaenoic acid compared to artificial sea salt, although the total lipid concentration was higher in microalgae cultured with artificial sea salt. The developed medium was validated through semi-continuous cultures in 100 L flat vertical bags, showing to be an economically viable alternative without hindering N. oculata growth.

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Application of response surface methodology (RSM) for optimizing biomass production in Nannochloropsis oculata UTEX 2164

Cited by 3 publications

References 85 publications

Response Surfaces Method and Artificial Intelligence Approaches for Modeling the Effects of Environmental Factors on Chlorophyll a in Isochrysis galbana

Response Surfaces Method and Artificial Intelligence Approaches for Modeling the Effects of Environmental Factors on Chlorophyll a in Isochrysis galbana

Production of Antioxidants and High Value Biomass from Nannochloropsis oculata: Effects of pH, Temperature and Light Period in Batch Photobioreactors

Alternative culture medium for Nannochloropsis oculata mass culture

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