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

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Abstract

Since the last few decennia microalgal biomass is of industrial significance for achieving sustainable biofuels pharmaceuticals, nutraceuticals, and functional foods. However, the major bottleneck that needs to be addressed for achieving sustainability is the low biomass productivity of microalgae. In this context, we employed a statistical approach, response surface methodology (RSM), for medium optimization to enhance the biomass of the marine strain Nannochloropsis oculata UTEX 2164 since N. oculata has good growth rate and lipid content along with other biochemical constituents. We investigated the role of macronutrients such as nitrogen (NaNO3—sodium nitrate as the source), phosphorus (NaH2PO4—monosodium phosphate as the source), and carbon (NaHCO3—sodium bicarbonate as the source) in F/2 medium as major factors that obviously control biomass production. The medium optimization was undertaken first to enhance algal biomass and the preliminary data analysis accounted for these quantifiable variables using the one-factor-at-a-time (OFAT) method with varying nitrogen, phosphorus, and carbon concentrations predicting their effect on the overall biomass yield. These findings were refined for the RSM-based experiments using a central composite design (CCD) and later evaluated to demonstrate the combined effect of nitrogen (N) and phosphorous (P) interactions by measuring biomass yields. Our data demonstrate that after nine days of culture with a 21.08 mg L−1 of N-NO3− concentration, the maximum biomass concentration achieved was 576 mg L−1, compared to 460 mg L−1 in the control. Overall, the employed statistical modeling achieved 25% DCW more biomass concentration than the control, with a coefficient of variance (CV) of 8.22%. Thus this study paves the way to further utilize this alga or the refined medium composition to acquire higher cell biomass in other algae.

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Data availability

All data generated or analyzed during this study are included in this published article. The raw data in the present study are available from the corresponding author on reasonable request.

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Funding

This work was supported by grants from the Department of Biotechnology (BT/PB/Center/03/2011-Phase II), Ministry of Science and Technology, Government of India (GoI), New Delhi, India. Senior Research Fellowship for AM supported from Council of Scientific & Industrial Research (CSIR), New Delhi, India, is duly acknowledged (09/512(0232)/2017-EMR-I).

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  1. Omics of Algae Group, Industrial Biotechnology, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi, 110067, India

    Anju Mehra & Pannaga Pavan Jutur

  2. DBT-ICGEB Centre for Advanced Bioenergy Research, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi, 110067, India

    Pannaga Pavan Jutur

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Anju Mehra: Conceptualization, Analysis, and Writing—Original Draft; Pannaga Pavan Jutur: Conceptualization, Funding acquisition, Supervision, Project administration, Writing—review & editing.

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Mehra, A., Jutur, P.P. Application of response surface methodology (RSM) for optimizing biomass production in Nannochloropsis oculata UTEX 2164. J Appl Phycol 34, 1893–1907 (2022). https://doi.org/10.1007/s10811-022-02774-3

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