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Artificial neural network modelling-coupled genetic algorithm optimization for co-production of bioethanol and xylitol from delignified elephant grass

Author

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  • Aishwarya Aishwarya
  • Arun Goyal

Abstract

The present study explores the potential of wild elephant grass (EG), for co-production of ethanol and xylitol. Alkaline H 2 O 2 -pretreated-EG was hydrolyzed by a tailor-made cocktail of recombinant bacterial crude cellulolytic and xylanolytic enzymes, used for co-fermentation. Candida tropicalis (MTCC 230) was adapted in medium having both C5 and C6 sugars. Three significant parameters, inoculum size, S:N in medium and orbital shaking speed (rpm), were optimized using response surface methodology (RSM) and artificial neural network linked genetic algorithm (ANN-GA) for bioethanol and xylitol production. The predictive capabilities of both models were compared. ANN-GA predicted optimum conditions were 10% (v/v) initial inoculum size, the S:N ratio 37.4 and rpm 250 gave 27.4 g/L (0.42 g/g glucose ) ethanol and 5.1 g/L (0.44 g/g xylose ) xylitol titres with K L a of 194 h −1 . The ANN-GA optimized parameters gave 22.3% and 13.3% higher ethanol and xylitol yields, respectively, than those predicted by the RSM-based model. The current innovative method of co-producing ethanol and xylitol from EG offers a promising alternative to traditional bioethanol production.

Suggested Citation

  • Aishwarya Aishwarya & Arun Goyal, 2025. "Artificial neural network modelling-coupled genetic algorithm optimization for co-production of bioethanol and xylitol from delignified elephant grass," Energy & Environment, , vol. 36(7), pages 3166-3183, November.
    • Handle: RePEc:sae:engenv:v:36:y:2025:i:7:p:3166-3183
    DOI: 10.1177/0958305X251367113
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    References listed on IDEAS

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    1. Ion LUNGU & Adela BÂRA & George CĂRUTASU & Alexandru PÎRJAN, & Simona-Vasilica OPREA, 2016. "Prediction Intelligent System In The Field Of Renewable Energies Through Neural Networks," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(1), pages 85-102.
    2. Mohapatra, Sonali & Mishra, Chinmaya & Behera, Sudhansu S. & Thatoi, Hrudayanath, 2017. "Application of pretreatment, fermentation and molecular techniques for enhancing bioethanol production from grass biomass – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 1007-1032.
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    1. Saravanan, Harini & Uppuluri, Kiran Babu, 2026. "Chemical-free processing of Bermuda grass for bioethanol production: Hybrid optimization of simultaneous C5/C6 sugar utilization using response surface methodology, genetic algorithm, and artificial neural network," Renewable Energy, Elsevier, vol. 258(C).

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