Biotechnology Letters

, Volume 39, Issue 5, pp 721–730 | Cite as

Maximizing power generation from dark fermentation effluents in microbial fuel cell by selective enrichment of exoelectrogens and optimization of anodic operational parameters

  • Jhansi L. Varanasi
  • Pallavi Sinha
  • Debabrata Das
Original Research Paper



To selectively enrich an electrogenic mixed consortium capable of utilizing dark fermentative effluents as substrates in microbial fuel cells and to further enhance the power outputs by optimization of influential anodic operational parameters.


A maximum power density of 1.4 W/m3 was obtained by an enriched mixed electrogenic consortium in microbial fuel cells using acetate as substrate. This was further increased to 5.43 W/m3 by optimization of influential anodic parameters. By utilizing dark fermentative effluents as substrates, the maximum power densities ranged from 5.2 to 6.2 W/m3 with an average COD removal efficiency of 75% and a columbic efficiency of 10.6%.


A simple strategy is provided for selective enrichment of electrogenic bacteria that can be used in microbial fuel cells for generating power from various dark fermentative effluents.


Anode Dark fermentation effluents Energy efficiency Exo-electrogens, Microbial fuel cell Volatile fatty acids 



The authors gratefully acknowledge Defence Research and Development Organisation (DRDO, Project Grant No. ERIP/ER/1200435/M/01/1489), Government of India for the financial assistance and IIT Kharagpur for the laboratory facilities.

Supporting Information

Supplementary methods: Cumulative effect of various parameters on power density of MFC;

ANOVA; Verification of Taguchi’s method

Supplementary Table 1—Basal media composition.

Supplementary Table 2—Acetate based synthetic wastewater media composition.

Supplementary Table 3—ANOVA Table for the anodic parameters.

Supplementary Fig. 1—Factor effect plot of pH, S/V ratio, anode distance and inlet COD concentration vs. power density of MFC.

Supplementary Fig. 2—Taguchi prediction analysis for the maximization of power density using optimized process parameters.

Supplementary material

10529_2017_2289_MOESM1_ESM.docx (234 kb)
Supplementary material 1 (DOCX 233 kb)


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Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  • Jhansi L. Varanasi
    • 1
  • Pallavi Sinha
    • 1
  • Debabrata Das
    • 1
  1. 1.Department of BiotechnologyIndian Institute of TechnologyKharagpurIndia

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