Fuzzy intelligence for investigating the correlation between growth performance and metabolic yields of a Chlorella sp. exposed to various flue gas schemes

Virthie Bhola, Feroz Mahomed Swalaha, Mahmoud Nasr, Faizal Bux

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

A Chlorella sp. was cultivated in a photobioreactor under different experimental conditions to investigate its acclimation to high-CO2 exposures. When the microalgae was grown under controlled flue gas sparging and optimised nutrients, the biomass concentration increased to 3.415 ± 0.145 g L−1 and the maximum protein yield was obtained (57.500 ± 0.351% w w−1). However, when the culture was exposed to continuous flue gas, the lowest biomass growth (1.665 ± 0.129 g L−1) was noted. Under these conditions, high carbohydrate and lipid values were recorded (38.600 ± 1.320% w w−1 and 30.200 ± 0.150% w w−1), respectively. A Sugeno-type fuzzy model was employed to understand the correlation between peak biomass concentration (Bmax), CO2 uptake rate (qCO2), and maximum relative electron transport rate (rETRmax) as inputs and carbohydrate, protein, and lipid yields as outputs. Results of the model were in agreement with the experimental data (r2-value >0.985).

Original languageEnglish
Pages (from-to)1078-1086
Number of pages9
JournalBioresource Technology
Volume243
DOIs
Publication statusPublished - 1 Jan 2017

    Fingerprint

Keywords

  • Cell metabolites
  • Chlorella sp.
  • Flue gas mixture
  • Fuzzy logic
  • Photosynthetic rate

ASJC Scopus subject areas

  • Bioengineering
  • Environmental Engineering
  • Renewable Energy, Sustainability and the Environment
  • Waste Management and Disposal

Cite this