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Anaerobic digestion performance and kinetics of biomass pretreated with various fungal strains utilizing exponential and sigmoidal equation models

Author

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  • Basinas, Panagiotis
  • Chamrádová, Kateřina
  • Rusín, Jiří
  • Kaldis, Sotiris P.

Abstract

Corn silage was pretreated with white rot fungi to optimize the methane generation capacity of biomass and the effect of the most important pretreatment parameters on the anaerobic digestion performance of material was determined by employing mathematical modelling. Pretreatment with selective fungi led to optimal increment in methane production from 0.301 m3kgVS−1 from corn silage to 0.465 m3kgVS−1 from the 10-day modified material, whereas non-selective fungi had negative effect. A reverse L-shape curve observed for the corn silage indicated an uninterrupted methane production and was not modified when the substrate was pretreated with Dichomitus squalens, Irpex lacteus and Trametes versicolor. Exponential models fitted L-curves better than sigmoidal equations with Cone model providing the most accurate predictions regardless of the selective or non-selective feature of the fungal strain used for the pretreatment of corn silage. Increasing pretreatment time led to a differentiation of the methane yield and adjustment of the curve shape to a stepped outline adequately modelled by Cone and transference models. Contrary to three-parameter sigmoidal models a fourth shape variable included in Richards equation was crucial, allowing for a flexible inflection point that enabled an accurate replication of an S-shape curve obtained for methane production from the hybrid substrate.

Suggested Citation

  • Basinas, Panagiotis & Chamrádová, Kateřina & Rusín, Jiří & Kaldis, Sotiris P., 2024. "Anaerobic digestion performance and kinetics of biomass pretreated with various fungal strains utilizing exponential and sigmoidal equation models," Renewable Energy, Elsevier, vol. 235(C).
  • Handle: RePEc:eee:renene:v:235:y:2024:i:c:s0960148124014587
    DOI: 10.1016/j.renene.2024.121390
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