Anaerobic conversion of Chromolaena odorata (Siam weed) to biogas

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 pre treatments. 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 ANN

Biochemical conversion of fruit rind of Telfairia occidentalis (fluted pumpkin) and poultry manure

Environmental pollution by solid wastes and inadequate energy supply are some of the major challenges facing the developing world. This study evaluated the potentials of Fluted pumpkin fruit rind and poultry manure for biogas generation. Mechanical and thermo-alkaline pre-treatments were applied to two samples labeled ‘O’ and ‘P’ while the third sample (Q) had no thermo-alkaline treatment. The physicochemical characteristics of the substrates revealed richness in nutrients and mineral elements. The results showed that use of a combination of pre-treatment methods enhanced the biogas yield in the pre-treated substrates. Analysis of the gas composition showed 66.5 ± 2.5% Methane, 25 ± 1% Carbon dioxide; 58.5 ± 2.5% Methane, 26 ± 1% Carbon dioxide; 54.5 ± 1.5% Methane, 28 ± 2% Carbon dioxide for the three experiments, respectively. All the obtained values show the models had a high predictive ability. The substrates should be further used for energy generatio