Enhancement of lipid accumulation in microalga Desmodesmus sp. VV2: Response Surface Methodology and Artificial Neural Network modeling for biodiesel production

Elamathi Vimali; Arumugasamy Senthil Kumar; Nagamalai Sakthi Vignesh; Balasubramaniem Ashokkumar; Amarajothi Dhakshinamoorthy; Aswathy Udayan; Muthu Arumugam; Arivalagan Pugazhendhi; Perumal Varalakshmi

doi:10.1016/j.chemosphere.2021.133477

Enhancement of lipid accumulation in microalga Desmodesmus sp. VV2: Response Surface Methodology and Artificial Neural Network modeling for biodiesel production

Chemosphere. 2022 Apr:293:133477. doi: 10.1016/j.chemosphere.2021.133477. Epub 2022 Jan 7.

Authors

Elamathi Vimali¹, Arumugasamy Senthil Kumar², Nagamalai Sakthi Vignesh¹, Balasubramaniem Ashokkumar³, Amarajothi Dhakshinamoorthy⁴, Aswathy Udayan⁵, Muthu Arumugam⁵, Arivalagan Pugazhendhi⁶, Perumal Varalakshmi⁷

Affiliations

¹ Department of Molecular Microbiology, School of Biotechnology, Madurai Kamaraj University, Madurai, 625021, Tamil Nadu, India.
² Department of Chemical and Environmental Engineering, University of Nottingham Malaysia, Jalan Broga, 43500, Semenyih, Selangor Darul Ehsan, Malaysia. Electronic address: Senthil.Arumugasamy@nottingham.edu.my.
³ Department of Genetic Engineering, School of Biotechnology, Madurai Kamaraj University, Madurai, 625021, Tamil Nadu, India.
⁴ School of Chemistry, Madurai Kamaraj University, Madurai, 625021, Tamil Nadu, India.
⁵ Microbial Processes and Technology Division, CSIR-National Institute for Interdisciplinary Science and Technology (NIIST), Trivandrum, Kerala, India.
⁶ College of Medical and Health Science, Asia University, Taichung, Taiwan; Center for Transdisciplinary Research (CFTR), Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, India.
⁷ Department of Molecular Microbiology, School of Biotechnology, Madurai Kamaraj University, Madurai, 625021, Tamil Nadu, India. Electronic address: vara5277@gmail.com.

PMID: 35007613
DOI: 10.1016/j.chemosphere.2021.133477

Abstract

Microalgae are the most attractive renewable energy sources for the production of biofuels because of their luxurious growth and lipid accumulation ability in diverse nutritional conditions. In the present study, Desmodesmus sp. VV2, an indigenous microalga, was evaluated for its biodiesel potential using Response Surface Methodology (RSM) to improve the lipid accumulation with the combination of nutrients stress NaNO₃ starvation, CaCl₂ depletion, and supplementation of magnesium oxide nanoparticles (MgO). Among different stress conditions, 57.6% lipid content was achieved from RSM optimized media. Owing to this, RSM results were also validated by the Artificial Neural Network (ANN) with 11 training algorithms and it is found that RSM was more significant. In addition, the saturated fatty acid (SFA) content was noticeably increased in RSM optimized media (95.8%) while compared with control. Further, the highest total FAME content 97.21% was also achieved in cells grown in RSM optimized media. Biodiesel quality parameters were analyzed and found that they are in accordance with international standards. Thus, this study suggesting that the fatty acid profile of Desmodesmus sp. VV2 attained under optimized media conditions would be suitable for biodiesel production for future energy demand.

Keywords: Artificial neural network; Biodiesel; Microalgae; Nutrient stress; Response surface methodology; Transesterification.

MeSH terms

Biofuels*
Biomass
Fatty Acids
Microalgae*
Neural Networks, Computer

Substances

Biofuels
Fatty Acids