Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/243552 
Year of Publication: 
2018
Citation: 
[Journal:] Energy Reports [ISSN:] 2352-4847 [Volume:] 4 [Publisher:] Elsevier [Place:] Amsterdam [Year:] 2018 [Pages:] 691-700
Publisher: 
Elsevier, Amsterdam
Abstract: 
This study evaluated the anaerobic mono-digestion of two different samples of Chromolaena odorata. Combinations of mechanical and thermo-alkaline pretreatments were applied to one of the two samples and labeled as "X" while the second had no thermo-alkaline treatment and was labeled as "Y". The Central Composite Design was used to design the pretreatments. The physicochemical characteristics of the substrates were carried out using standard methods after appropriate pretreatments. From the experimental set-ups, the most probable actual biogas yields in experiments "X" and "Y" were 0.3554 m3/kg Total Solid (TS)fed and 0.1803 m3/kg TSfed with the desirability of 99 and 100%, respectively. Further shown in the result is a 49.2% higher experimental (actual) biogas yield in experiment "X" over "Y". Gas chromatographic analysis revealed the CH4 and CO2 content of both experiments to be 65 ± 1.5%; 21 ± 3% and 53.5 ± 2.5%; 26 ± 3%, respectively. Combination of different pretreatment methods enhanced enormous biogas yield from the digested substrates. Optimization of the generated biogas data was carried out using the Response Surface Methodology (RSM) and the Artificial Neural Networks (ANNs). The coefficient of determination (R2) for RSM was lower compared to that of ANN. This shows that ANNs model gives higher accuracy than RSM model. Further utilization of this weed for biogas production is encouraged by the results from this study.
Subjects: 
Optimization
Anaerobic digestion
Lignocellulosic biomass
Methane
Pretreatment
Siam weed
Persistent Identifier of the first edition: 
Creative Commons License: 
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Document Type: 
Article
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