Optimization of biogas yield from anaerobic co-digestion of corn-chaff and cow dung digestate: RSM and python approach

The utilization of various feedstocks of unique characteristics in producing biogas could potentially enhance the application of clean fuel from biomass wastes. Two modelling tools were used to explore biogas production from plant and animal wastes. In this study, corn chaff was inoculated with cow...

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Autores principales:	Sunday Chukwuka Iweka, K.C. Owuama, J.L. Chukwuneke, O.A. Falowo
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Cow dung digestate Anaerobic digestion Corn chaff Biogas production Optimization Python coding Science (General) Q1-390 Social sciences (General) H1-99
Acceso en línea:	https://doaj.org/article/2a3069d4638d47008b76b0a0afd6ea23
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spelling	oai:doaj.org-article:2a3069d4638d47008b76b0a0afd6ea232021-12-02T05:02:18ZOptimization of biogas yield from anaerobic co-digestion of corn-chaff and cow dung digestate: RSM and python approach2405-844010.1016/j.heliyon.2021.e08255https://doaj.org/article/2a3069d4638d47008b76b0a0afd6ea232021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2405844021023586https://doaj.org/toc/2405-8440The utilization of various feedstocks of unique characteristics in producing biogas could potentially enhance the application of clean fuel from biomass wastes. Two modelling tools were used to explore biogas production from plant and animal wastes. In this study, corn chaff was inoculated with cow dung digestate using different mixing ratios of substrate/inoculum (S/I) of 1:1, 1:1.55, and 1:3.5 for hydraulic retention time (HRT) of 25, 31, and 37 days as modelled using Central Composite Design (Face Centered Design) to optimize the process and predict the optimal response. The result shows that the mixture ratio of 1:1.55 for 37 days gave a cumulative highest biogas yield of 6.19 L under mesophilic conditions. The model p-value is <0.0001, an indication that the model term is significant. The python coding of the input factors gave the optimal value of 4.71 L, which is similar to the result obtained via CCD. Thus, both CCD (Face Centered Design) and python coding are reliable in the optimization of biogas production as they both predicted the same optimal values and approximately the same highest cumulative biogas yield. The GC-MS characterization of produced biogas revealed that it contains 68% methane and 22.76% CO2. Other constituents present are confirmed by FTIR analysis results. The methane in produced biogas has a flashpoint of -182 °C, which is extremely flammable. This data shows that both CCD and python coding can model biogas production with high accuracy and biogas produced can be used for heating purposes.Sunday Chukwuka IwekaK.C. OwuamaJ.L. ChukwunekeO.A. FalowoElsevierarticleCow dung digestateAnaerobic digestionCorn chaffBiogas productionOptimizationPython codingScience (General)Q1-390Social sciences (General)H1-99ENHeliyon, Vol 7, Iss 11, Pp e08255- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Cow dung digestate Anaerobic digestion Corn chaff Biogas production Optimization Python coding Science (General) Q1-390 Social sciences (General) H1-99
spellingShingle	Cow dung digestate Anaerobic digestion Corn chaff Biogas production Optimization Python coding Science (General) Q1-390 Social sciences (General) H1-99 Sunday Chukwuka Iweka K.C. Owuama J.L. Chukwuneke O.A. Falowo Optimization of biogas yield from anaerobic co-digestion of corn-chaff and cow dung digestate: RSM and python approach
description	The utilization of various feedstocks of unique characteristics in producing biogas could potentially enhance the application of clean fuel from biomass wastes. Two modelling tools were used to explore biogas production from plant and animal wastes. In this study, corn chaff was inoculated with cow dung digestate using different mixing ratios of substrate/inoculum (S/I) of 1:1, 1:1.55, and 1:3.5 for hydraulic retention time (HRT) of 25, 31, and 37 days as modelled using Central Composite Design (Face Centered Design) to optimize the process and predict the optimal response. The result shows that the mixture ratio of 1:1.55 for 37 days gave a cumulative highest biogas yield of 6.19 L under mesophilic conditions. The model p-value is <0.0001, an indication that the model term is significant. The python coding of the input factors gave the optimal value of 4.71 L, which is similar to the result obtained via CCD. Thus, both CCD (Face Centered Design) and python coding are reliable in the optimization of biogas production as they both predicted the same optimal values and approximately the same highest cumulative biogas yield. The GC-MS characterization of produced biogas revealed that it contains 68% methane and 22.76% CO2. Other constituents present are confirmed by FTIR analysis results. The methane in produced biogas has a flashpoint of -182 °C, which is extremely flammable. This data shows that both CCD and python coding can model biogas production with high accuracy and biogas produced can be used for heating purposes.
format	article
author	Sunday Chukwuka Iweka K.C. Owuama J.L. Chukwuneke O.A. Falowo
author_facet	Sunday Chukwuka Iweka K.C. Owuama J.L. Chukwuneke O.A. Falowo
author_sort	Sunday Chukwuka Iweka
title	Optimization of biogas yield from anaerobic co-digestion of corn-chaff and cow dung digestate: RSM and python approach
title_short	Optimization of biogas yield from anaerobic co-digestion of corn-chaff and cow dung digestate: RSM and python approach
title_full	Optimization of biogas yield from anaerobic co-digestion of corn-chaff and cow dung digestate: RSM and python approach
title_fullStr	Optimization of biogas yield from anaerobic co-digestion of corn-chaff and cow dung digestate: RSM and python approach
title_full_unstemmed	Optimization of biogas yield from anaerobic co-digestion of corn-chaff and cow dung digestate: RSM and python approach
title_sort	optimization of biogas yield from anaerobic co-digestion of corn-chaff and cow dung digestate: rsm and python approach
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/2a3069d4638d47008b76b0a0afd6ea23
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Optimization of biogas yield from anaerobic co-digestion of corn-chaff and cow dung digestate: RSM and python approach

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