Multi-objective genetic algorithm optimization of energy efficiency and biomass concentration of Synechococcus HS-9 cultivation for third-generation biodiesel feedstock

Arif Rahman, Kania Dyah Nastiti, Nining Betawati Prihantini, M. A.M. Oktaufik, Surat Indrijarso, Alfred Kampira Levison, Ridho Irwansyah, N. Nasruddin

Research output: Contribution to journalArticlepeer-review

Abstract

Microalgae is a sustainable biological resource since it can be used in biodiesel production, pharmaceutical development, nutritional supplements, carbon dioxide sequestration, and wastewater remediation. Due to its high lipid content and low carbon dioxide emissions, microalgae-derived biodiesel can replace fossil fuels. Microalgae biomass production involves cultivation, harvesting, and drying. To develop microalgae and produce high-quality biomass, culture procedures must be optimized. Microalgae cultivation is affected by a range of physical and chemical parameters, including light intensity (I), temperature (T), carbon dioxide (CO2), pH, dissolved oxygen (DO), and oxidation reduction potential (ORP). The objective of this study is to examine the impact of physico-chemical factors on the cultivation process of Synechococcus HS-9 in order to generate dry biomass. ANN and multi-objective genetic algorithms will also be used to optimize cultivation. The five main procedures of this study are: 1) preparation of the cultivation medium; 2) Synechococcus HS-9 inoculum and utilization of a photobioreactor; 3) inoculation; 4) cultivation and physical-chemical parameter data collection; and 5) prediction and optimization. The physico-chemical properties of Synechococcus HS-9 were measured during cultivation. The average values of these parameters were found to be 439 to 325 7 μmol m−2s−1 for light conditions and 190–200 μmol m−2s−1 for dark conditions. During cultivation, T ranged from 29 to 32 °C and CO2 from 82 to 84 ppm. Most pH levels are between 8 and 7.5. The dissolved oxygen (DO) concentration drops from 15 to 3 mg/l. The ORP also fluctuates, dropping from 170 mV to 155 mV and then rising to 180 mV. Based on multi-objective optimization, the optimal values for energy efficiency (ղ) and biomass concentration (C) are 0.043 % and 4.61 × 10−5 mg/ml, respectively. The optimal condition is achieved when the light intensity (I): 254.7 μmol m−2s−1, temperature (T): 29.7 °C, CO2 concentration: 83.4 ppm, pH: 8.6, dissolved oxygen (DO): 6.0 mg/l, and ORP: 149.1 mV.

Original languageEnglish
Article number100614
JournalCase Studies in Chemical and Environmental Engineering
Volume9
DOIs
Publication statusPublished - Jun 2024

Keywords

  • Artificial neural network
  • Biomass production
  • Genetic algorithm
  • Microalgae
  • Multi – Objective optimization
  • Synechococcus HS-9

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