- Tytuł:
- Optimization of slurry ratio and sonication time on biogas production from chicken droppings
- Autorzy:
-
Abubakar, Ibrahim K.
Ibrahim, Aminu
Muhammad, Yusuf Y. - Powiązania:
- https://bibliotekanauki.pl/articles/16648113.pdf
- Data publikacji:
- 2022
- Wydawca:
- Polska Akademia Nauk. Czasopisma i Monografie PAN
- Tematy:
-
optimization
response surface methodology
biogas production
chicken droppings
ultrasonic pretreatment - Opis:
- Background. A research was conducted on the ultrasonic pretreatment of chicken droppings for biogas production. The hydrolysis step in anaerobic digestion is rate-limiting and time-consuming due to the presence of complex molecules in the organic wastes. Pretreatment encourages faster digestion and yields improvement by making the organic waste ready for microbial attack. Material and methods. To achieve the optimum sonication time and slurry ratio for maximum biogas production, Response Surface Methodology (RSM) was used in this study. 13 experimental runs were developed according to Central Composite Design with different setup conditions and five replicates at center points to observe the Response, i.e., volumes of biogas produced. This was achieved with the aid of a software package (Design Expert 12.0.1.0). A quadratic model was developed for the responses and a 3D response surface plot was obtained to analyze the effect of the variables and their interactions to determine their optimum levels. Results. The numerical optimization and point prediction result gave a sonication time of 18.6 minutes and a slurry ratio of 2.0 (i.e., 2.0 : 1.0). Under this condition, the predicted maximum volume of biogas production is 24.514 ml in 12 days. This prediction was tested and validated, and the volume of biogas produced under the same conditions was 22.282 ml. This confirmed the adequacy of the predicted model as only a 10.02% error was recorded. Conclusions. Henceforth, the optimum sonication time and slurry ratio were achieved for maximum biogas production from chicken droppings.
- Źródło:
-
BioTechnologia. Journal of Biotechnology Computational Biology and Bionanotechnology; 2022, 103, 3; 261-268
0860-7796 - Pojawia się w:
- BioTechnologia. Journal of Biotechnology Computational Biology and Bionanotechnology
- Dostawca treści:
- Biblioteka Nauki
Artykuł