Experimental and Artificial Intelligence Modelling Study of Oil Palm Trunk Sap Fermentation

Autor: Leila Ezzatzadegan, Rubiyah Yusof, Noor Azian Morad, Parvaneh Shabanzadeh, Nur Syuhana Muda, Tohid N. Borhani
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Energies, Vol 14, Iss 8, p 2137 (2021)
Druh dokumentu: article
ISSN: 1996-1073
DOI: 10.3390/en14082137
Popis: Five major operations for the conversion of lignocellulosic biomasses into bioethanol are pre-treatment, detoxification, hydrolysis, fermentation, and distillation. The fermentation process is a significant biological step to transform lignocellulose into biofuel. The interactions of biochemical networks and their uncertainty and nonlinearity that occur during fermentation processes are major problems for experts developing accurate bioprocess models. In this study, mechanical processing and pre-treatment on the palm trunk were done before fermentation. Analysis was performed on the fresh palm sap and the fermented sap to determine the composition. The analysis for total sugar content was done using high-performance liquid chromatography (HPLC) and the percentage of alcohols by volume was determined using gas chromatography (GC). A model was also developed for the fermentation process based on the Adaptive-Network-Fuzzy Inference System (ANFIS) combined with particle swarm optimization (PSO) to predict bioethanol production in biomass fermentation of oil palm trunk sap. The model was used to find the best experimental conditions to achieve the maximum bioethanol concentration. Graphical sensitivity analysis techniques were also used to identify the most effective parameters in the bioethanol process.
Databáze: Directory of Open Access Journals