A Comparative Study of Biogas produced from selected Animal Wastes at less-populated settlements in Awka North and South Local Government Area in Anambra State, South-East Nigeria.

A Comparative Study of Biogas produced from selected Animal Wastes at less-populated settlements in Awka North and South Local Government Area in Anambra State, South-East Nigeria. | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Comparative Study of Biogas produced from selected Animal Wastes at less-populated settlements in Awka North and South Local Government Area in Anambra State, South-East Nigeria. Onyinyechukwuka G. UGWUOKE, Uche O. CHUKWURA-OSOAGBA, Vivian N. ANAKWENZE, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7491747/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract Background Biogas is a renewable source of energy generated from anaerobic digestion of biomass. A comparative analyses of biogas produced from anaerobic digestion of animal wastes (cow dung, goat droppings and chicken droppings) in Awka North and South Local Government Area, Nigeria were studied. Methods Laboratory scale digesters (1000 cm 3 conical flasks) were used for the anaerobic digestion with retention period of 30 days and the experiment was carried out at room temperature. The biogas produced was trapped in inverted measuring glass cylinder to get the volume of gas produced and in poly vinyl chloride ball to hold the biogas for analysis of its constituent compositions. The animal wastes were mixed with water in the ratio of 1:2. Data were analyzed using ANOVA. Results Twenty bacteria genera belonging to six phyla including Firmicutes, Proteobacteria, Bacillota, Actinomycetota, Spirochaetota and Bacteroidota were identified to be involved in the anaerobic digestion process using 16S rRNA targeted genomic sequencing. The findings revealed the cumulative biogas yield by chicken droppings (CnD), cow dung (CwD), goat droppings (GtD), cow dung – chicken droppings, cow dung – goat droppings, chicken droppings – goat droppings and cow dung – chicken droppings – goat droppings were 5472 cm 3 , 1546 cm 3 and 2072 cm 3, 4607 cm 3 , 1253 cm 3 , 4788 cm 3 and 4111 cm 3 respectively. Biogas slurries for anaerobic digestion of animal wastes (cow dung, chicken droppings and goat droppings) were prepared in 3 designs (first digester without dark covering, second digester with dark covering and the third digester has dark covering with their pH raised to pH 8) with all the animal wastes producing highest percentage (CnD 70.43%, GtD 75.57%, CwD 76.96%) of methane (CH 4 ) at the digesters with dark covering at pH 8. Statistical analysis on ANOVA reveals the biogas compositions of the animal wastes shows that they were not significant at p co-digestion of chicken droppings and goats dropping > co-digestion of cow dropping and chicken droppings. These animal wastes produced highest percentage of methane gas at alkaline pH with dark covering. The chicken dropping with the highest biogas yield could be a good source for energy resource alternative, and or curb control for groundwater contamination, or used to reduce organic waste in landfills. Biogas methane bacteria contaminant animal waste anaerobic digestion Figures Figure 1 Figure 2 Figure 3 Figure 4 1.0 Introduction The accumulation and management of wastes in the environment has raised concerns because of the problems associated with waste disposal into the wider environment [ 1 ]. The conventional methods mostly used for the management and treatment of wastes have some demerits it poses to the environment [ 2 ]. These methods of waste disposal cause environmental problems like uncontrolled release of methane and similar persistent organic pollutants (POPs) into the atmosphere, producing unpleasant odors and spread of pathogenic microorganisms [ 3 , 4 ]. The main aim of a waste management system is to potentially remove, or at least reduce to the minimum the negative effects on public health and/or the environment, it contributes to sustainability factors; and provides a net positive energy outcome [ 5 ]. Waste materials such as manure and various crop wastes are perfect candidates for energy production [ 6 ]. Organic wastes are reservoirs of carbon resources for energy production. The challenge in utilizing the economic and environmental viability of organic wastes is gaining an understanding of the waste production, characteristics, diversion and preprocessing methods, transport requirements, available conversion technologies and the overall energy production [ 5 ]. Considering various alternative energy sources, biomass has been an indispensable part of energy debate [ 7 ]. In fact, biomass plays a significant role as source of renewable energy, with huge potentials in the production of biofuels for transportation, electricity and heat [ 8 , 9 ]. Biogas is obtained from the anaerobic breakdown of biomass by microorganisms. Biogas is a renewable energy source which has effective effects on nature [ 10 ]. The anaerobic digestion process goes through four stages, which are hydrolysis, acidogenesis, acetogenesis and methagenesis [ 11 , 10 ], and the organisms involved in each stage are referred to as hydrolyser, acidogen, acetogen and methanogen respectively [ 12 ]. Biogas consists mainly of methane and carbon dioxide together with other gases and vapours in small proportion such as hydrogen sulfide, hydrogen, water vapour, nitrogen and volatile organic compounds [ 10 , 13 ]. Therefore, the high concentration of methane makes biogas an attractive fuel and it is used in solving an emission problem since methane is several times more harmful than carbon dioxide [ 14 ]. Improper disposal of wastes and poor waste management has created environmental menace that is hazardous to both the environment and humans. The aim of this study is examine and characterize biogas produced from cow dung, goat droppings and chicken droppings in Awka North and South Local Government Area for energy production. The objectives of the study are to characterize the bacteria involved in biogas production; determine the volume of biogas produced and determine the compositions of biogas. 2.0 The Study Area 2.1 Location, climate and geology of the study area The study areas, Gariki, Amansea are located in Awka North Local Government Area, and Commissioners quarters in Awka South Local Government Area, are both in Anambra State, situated in the Anambra Basin of the Benue Trough in Nigeria. Generally, the Anambra Basin is referred to as Cretaceous/Tertiary basin, integration between the Benue Trough (Cretaceous) and Niger Delta basin (Tertiary) [ 15 , 16 ]. The basin is bordered to the east by the Abakaliki anticlinorium, to the north and northwest by the basement rock and Benue hinge line respectively. Awka North lies between latitude 6 o 14’51”N and longitude 7 o 08’14”E, while Awka South lies between latitude 6 o 14’36”N and longitude 7 o 05’41”E in the Southeastern region of Nigeria (Fig. 1 ). There are two main seasons influenced in the areas, namely the dry and dusty harmattan season, and the wet season. The dry and dusty harmattan is usually between Novembers to March, while the wet season is between Aprils to October yearly. The Anambra Basin is dominantly filled with sediments (clastic) comprising of numerous lithostratigraphic units of thickness about 2500m, with several Formations and from upper Campanian to Recent in age [ 17 , 18 ]. The lithostratigraphic units consist of Nkporo Shale, Mamu, Ajali Sandstone, Nsukka, Imo Shale, Ameki, Nanka Sands, Ogwashi-Asaba, the Alluvial Plain Sands and Benin Formations. With the source of the sediments into the basin from the Cameroon massif and the Abakaliki synclinorium [ 19 , 18 ]. The study area, Awka North is predominantly underlain by Imo Shale, and characterized by undulating topography and distribution of the water drainage, vegetation, and formation of soils. The pattern of the drainage is referred as dendritic, consisting of regions with relatively homogeneous rock types, and relief of moderate to high degree [ 20 ]. 3.0 Materials and Methods 3.1 Sample Collection Animal wastes including fresh cow dung and goat droppings were collected from Gariki, Amansea, in Awka North, while fresh chicken droppings were collected from Iweama’s poultry farm at Commissioners quarters in Awka South LGA, Anambra state (Fig. 2). The samples were taken to Microbiology laboratory in sterile containers for analyses. 3.2 Identification of Bacteria from Samples After the anaerobic digestion, the slurry was shaken gently and the supernatant taken for sequencing. The bacteria in the digested slurry were identified using targeted metagenomic sequencing on the 16S specific region from bacteria in the slurry. 3.3 Digester design The bio-digester was designed using the method described by Tambuwal and Ogbiko [21]. One liter (1000cm 3 ) conical flasks were used as the bio-digesters. The digester was covered with a stopper in such a way to make it airtight. A hole was bored on the stopper through which a polyvinylchloride pipe was connected to allow the passage of biogas. The biogas produced were passed through a polyvinylchloride pipe and collected in a polyvinylchloride ball (for qualitative analysis). Whereas, the gases that were not collected directly in a polyvinylchloride ball, were collected using inverted measuring cylinder (for quantitative analysis). The digesters were operated at ambient (room) temperature in the mesophilic range with a retention time of 30 days. 3.4 Measurement and Analysis of biogas produced The volume of biogas produced was measured using the procedure of Tambuwal and Ogbiko [21]. The volume of biogas produced was measured daily by finding the volume of water displaced (downward displacement of water) by the gas in the inverted measuring cylinder that served as biogas collection system. The water used for trapping the biogas was acidified with 2% H 2 SO 4. Biogas analysis was done using Gas Chromatography (GC) analysis. 3.5 Slurry Preparation and loading of digester for semi-solid animal wastes (individually and when in combinations) The combination ratio of waste and water, with the combination ratio of the different wastes was done by slight modification of the method used by Ofoefule and Uzodinma [22]. The slurry was prepared by mixing the semi-solid animal wastes with water in the ratio of 1:2. Biogas produced by inverted glass measuring cylinder: For the measurement of biogas produced using inverted glass measuring cylinder, the quantity of semi-solid animal waste used was 300g, while the volume of water was 600ml. Below are the formulations for the preparation of the animal slurry. i. Cow dung = 300g ii. Chicken droppings = 300g iii. Goat droppings = 300g iv. Cow dung + Chicken droppings = 150g +150g v. Cow dung + Goat droppings = 150g + 150g vi. Chicken droppings + Goat droppings = 150g + 150g vii. Cow dung + Chicken droppings + Goat droppings = 100g + 100g + 100g Biogas produced by GC analysis: For the measurement of biogas produced using GC analysis, the quantity of semi-solid animal waste used was 300g, while the volume of water is 600mL. The digesters were prepared in three (3) groups, (a) those without dark covering, (b) those with dark covering, and (c) those with dark covering with its pH raised to pH 8. Below is the formulation for the preparation of the animal slurry. i. Cow dung = 300g ii. Chicken droppings = 300g iii. Goat dropping = 300g 3.6 Data analysis Statistical analysis was done using SPSS software version 20.0, and the data was analyzed. Data from gas chromatographic analysis for biogas produced from the chicken droppings, goat droppings and cow dung were compared using ANOVA. Tukey HSD comparison tests were used to evaluate the differences between and within treatments of various animal wastes, using a 5 % significance level ( p < 0.05). 4.0 Results and Discussion 4.1 Bacteria involved in biogas production Bacteria from 6 phyla, 20 genera, totaling 75 species were identified to be involved in the biogas production using targeted metagenomics sequencing on the 16S specific region from bacteria in the slurry (Table 1 ). The genera identified are Caproicibacterium, Burkholderia, Lactobacillus, Escherichia, Listeria, Veillonella, Clostridium, Bacillus, Pseudomonas, Cellulosilyticum, Prevotella, Romboutsia, Staphylococcus, Klebsiella, Enterococcus, Limosilactobacillus, Niameybacter, Salmonella, Caproiciproducens and Triponema. These genera belong to 6 phyla namely Proteobacteria, Bacteroidota, Bacillota, Actinomycetota, Spirochaetota and Firmicutes. The genera with the highest number of species are Clostridium, Lactobacillus and Limosilactobacillus with 13, 11 and 10 species respectively, whereas, Burkholderia, Veillonella, Pseudomonas, Cellulosilyticum, Prevotella, Romboutsia, Enterococcus and Caproiciproducens genera have one species each (Table 1 ). The metagenomic data shows that the phylum Firmicutes has the most bacteria diversity with the largest number of genera. The genera Burkholderia (Phylum Proteobacteria) is the genera with the highest mean relative abundance followed by Escherichia (Phylum Proteobacteria) and Caproicibacterium (Phylum Firmicutes). Table 1 Result of targeted genomic sequencing (16S RNA sequencing) SN Phylum Genus Species 1 Firmicutes Caproicibacterium C. amylolyticum, C. sp900184925, C. sp902809935, C. sp004103755 , 2 Proteobacteria Burkholderia B. lata 3 Firmicutes Lactobacillus L. johnsonii, L. gallinarum, L. delbrueckii, L. crispatus, L. amylovorus, L. gigeriorum, L. kitasatonis, L. paragasseri, L. equicursoris, L. gasseri, L. prophage , 4 Proteobacteria Escherichia E. coli, E. fergusonii , 5 Firmicutes Listeria L. monocytogenes, L. monocytogenes B, L. marthii , 6 Firmicutes Veillonella V. magna 7 Firmicutes Clostridium C. cuniculi, C. luticellarii, C. tertium, C. tyrobutyricum, C. baratii, C. beijerinckii, C. butyricum, C. neonatale, C. nigeriense, C. paraputrificum, C. sartagoforme, C. sartagoforme A, C. saudiense, C. sp000753455, C. sp014836325, C. sp015555905, C. sp902809985 , 8 Firmicutes Bacillus B. spizizenii, B. vallismortis, B. intestinalis, B. nakamurai, B. sp010093085 , 9 Proteobacteria Pseudomonas P. aeruginosa , 10 Firmicutes Cellulosilyticum C. lentocellum , 11 Bacteroidota Prevotella P. sp017347605 , 12 Firmicutes Romboutsia R. ilealis , 13 Bacillota Staphylococcus S. aureus, S. phage , 14 Proteobacteria Klebsiella K. aerogenes, K. quasipneumoniae, K. variicola, K. africana, K. granulomatis, K. pneumoniae , 15 Bacillota Enterococcus E. faecalis 16 Bacillota Limosilactobacillus L. antri, L. fermentum, L. ingluviei, L. mucosae, L. oris, L. pontis, L. reuteri, L. reuteri E, L. secaliphilus, L. vaginalis , 17 Actinomycetota Niameybacter N. massiliensis, N. stercoravium massiliensis 18 Proteobacteria Salmonella S. enterica, S. phage, S. virus 19 Firmicutes Caproiciproducens C. galactitolivorans 20 Spirochaetota Triponema T. parvum, T. D sp900769975 4.2 Physico-chemical properties of animal wastes Physico chemical properties of cow dung, chicken droppings and goat droppings are shown in Table 2 . Cow dung has the highest moisture content (73.36%), followed by chicken droppings and goat having the least moisture. Goat droppings have the least ash content (7.51%) among the three animal wastes. Cow dung has the least fibre content (1.81%) and least total solids (26.65%) compared to chicken droppings and goat droppings. Chicken droppings have the highest percentage of nitrogen (4.03%) and cow dung has the highest percentage of volatile solids. Total organic carbon is highest in cow dung and lowest in goat droppings. Table 2 Physico-chemical properties of semi-solid animal wastes (chicken droppings, cow dung and goat droppings). S/No Parameters Chicken dropping Cow dung Goat dropping 1 Moisture content (%) 59.10 73.36 57.32 2 Ash content (%) 9.30 9.60 7.51 3 Fibre content (%) 3.05 1.81 2.83 4 Total Solids (%) 40.90 26.65 42.68 5 Total Nitrogen (%) 4.03 3.75 3.47 6 Volatile Solids (%) 1.82 2.08 1.03 7 Total Organic Carbon (mg/kg) 1.67 1.98 1.46 9 Carbon - Nitrogen ratio 0.42 0.95 0.42 Volume of biogas yield from semi solid animal wastes (cumulative volume and volumes at every 5-day interval) Cumulative volumes of biogas yield by animal wastes The total volumes of biogas produced by semi solid animal wastes individually and in combination are shown in Fig. 3 . Individually, chicken droppings produced the highest volume of biogas (5,472 cm 3 ), followed by goat droppings (2,072 cm 3 ), whereas, cow dung gave the least volume of biogas (1,546 cm 3 ). When the animal wastes were combined, chicken droppings + goat droppings combination produced the highest volume (4,788 cm 3 ) of biogas, while cow dung + goat droppings combination produced the lowest volume (1,253 cm 3 ) of biogas ( Appendix 1). Generally, Fig. 3 shows that chicken droppings produced the highest volume of biogas, followed by the chicken droppings - goat droppings combination, while the cow dung - goat droppings combination produced the lowest volume of biogas. V olumes of biogas yields at interval of 5 days Biogas production by semi solid animal wastes were higher in the first 15 days of the retention period and lower in the second 15 days (Fig. 4 ). Generally, the volume of biogas produced decreased as the days passed. Cow dung has the highest biogas yield on the day 6 to day 10 retention period ( Appendix 1). The volume of biogas produced from day 21 to day 25 retention period were higher than the volume produced from the previous 5 days for chicken droppings, goat droppings, cow dung - goat droppings combination, chicken droppings - goat droppings combination and cow dung - chicken droppings - goat dropping combination (Fig. 4 ). Composition of biogas produced by chicken droppings Biogas from anaerobic digestion of chicken droppings from three different slurries (a: slurry at pH 6.8, without dark covering; b: slurry at pH 6.8, with dark covering; and c: slurry with pH raised to pH 8.0, with dark covering) were analyzed using gas chromatography (GC) (Table 3 ). The slurry prepared at pH 8.0, produced the highest percentage of methane gas (CH 4 ) (70.43%), whereas, the slurry without dark covering has the least percentage of CH 4 (60.30%) as indicated in their biogas compositions. The slurry that produced the highest percentage of carbon dioxide (CO 2 ) (22.36%) is the slurry without dark covering, while the slurry with dark covering prepared at pH 6.8 has the least percentage of CO 2 (15.43%) in the biogas produced. Table 3 Gas chromatographic analysis of biogas produced from Chicken droppings Constituents % Composition of biogas constituents A (pH 6.8) B (pH 6.8) C (pH 8.0) CO 0.16 0.25 0.27 CO 2 22.36 15.43 17.15 Ethanol 0.29 0.33 - Ethyl Acetate 1.05 0.99 0.79 Hydrogen Sulphide 0.87 1.04 1.15 Methane 60.30 68.02 70.43 Acetic Acid 2.78 2.76 - Acetonitrile 1.24 1.11 1.41 Acetone 0.93 1.12 1.24 Phenol 7.28 6.56 7.57 Methanol 2.74 2.39 - Keys: A: the digester at pH 6.8 without dark covering B: the digester at pH 6.8, with dark covering C: the digester at pH 8.0, with dark covering Composition of biogas produced by goat droppings Biogas analyses from anaerobic digestion of three different slurries of goat droppings (a: slurry at pH 7.3, without dark covering; b: slurry at pH 7.3, with dark covering; and c: slurry with pH raised to pH 8.0, with dark covering) showed that slurry prepared at pH 8.0 gave the highest percentage of CH 4 (75.57%), while the slurry with dark covering at pH 7.3 has the least percentage of CH 4 (72.53%) (Table 4 ). The GC results also showed that oxygen molecules (0.90%) were present in the biogas produced from the slurry with dark covering at pH 7.3. CO 2 was found to be lowest (21.28%) in the slurry prepared at pH 8.0 and highest (21.58%) in the slurry without dark covering at pH 7.3. Table 4 Gas chromatographic analysis of biogas produced from Goat droppings Constituents % Composition of biogas constituents A (pH 7.3) B (pH 7.3) C (pH 8.0) Lactic Acid 0.19 1.72 0.07 CO 2 21.58 21.54 21.28 Ethanol 1.60 1.16 1.68 Methane 75.37 72.53 75.57 Acetic Acid 0.21 0.06 0.24 Acetonitrile 0.90 0.66 1.04 Acetone 0.14 0.18 0.12 Oxygen - 0.90 - Benzaldehyde - 0.10 - Methanol - 1.15 - Keys: A: the digester at pH 7.3 without dark covering B: the digester at pH 7.3, with dark covering C: the digester at pH 8.0, with dark covering Composition of biogas produced by cow dung GC analyses of biogas produced from cow dung digestion (a: slurry at pH 6.9, without dark covering; b: slurry at pH 6.9, with dark covering; and c: slurry with pH raised to pH 8.0, with dark covering) showed that slurry with pH 8.0, with dark covering has the highest CH 4 concentration (76.96%), whereas, the slurry prepared at pH 6.9, with dark covering produced the least CH 4 concentration (61.99%) (Table 5 ). The slurry prepared at pH 8.0, with dark covering has the least concentration of CO 2 (11.72%), whereas the slurry prepared at pH 6.9 with dark covering has the highest concentration of CO 2 (15.18%). Table 5 Gas chromatographic analysis report of biogas produced from Cow dung Constituents % Composition of biogas constituents A (pH 6.9) B (pH 6.9) C (pH 8.0) Acetic acid 0.79 6.73 0.77 CO 2 12.67 15.18 11.72 Phenol 1.96 0.45 0.42 Acetone 2.08 0.40 - Ethanol 3.53 1.18 3.99 Methane 70.04 61.99 76.96 SO 2 2.15 3.87 - Chloroform 2.43 0.24 - CO 4.36 8.67 2.71 Methanol - 1.29 3.15 Ethyl Acetate - - 0.29 Keys: A: the digester at pH 6.9 without dark covering B: the digester at pH 6.9, with dark covering C: the digester at pH 8.0, with dark covering 4.3 Discussion Proteobacteria, Firmicutes, Bacteroidetes and Actinobacteria have been reported as the four phyla that led bacterial domain in read relative abundance among biogas producing microbial composition [ 23 , 24 ]. The above findings are in line with the result of this study which shows that the bacteria involved in the anaerobic digestion of animal slurry are from the phyla Proteobacteria, Firmicutes and Bacteroidota (Table 1 ). It has been shown that for treatment of solid feedstocks, the community is usually dominated by Firmicutes [ 25 , 26 , 27 , 28 ], while Stoyancheva et al . [ 24 ], also reported Firmicutes as a stable phylum during liquid manure and corn steep liquor treatment. The metagenomic data from this study confirmed that Firmicutes has a stable occurrence, but it also shows that Proteobacteria has more dominance in the digester. Studies associated with the digestion of liquid feedstocks as sludge have reported Proteobacteria, Firmicutes and Bacteroidetes as dominant bacterial phyla, followed by Actinobacteria and Chloroflexi [ 29 , 30 ]. This is in line with the result of this experiment which shows that the phylum Proteobacteria is the most abundant phylum compared to the other two phyla, which is also in agreement with the findings of Senes-Guerrero et al . [ 23 ], and Stoyancheva et al . [ 24 ]. Moisture contents of cow dung have been shown to be higher than those of chicken droppings and goat droppings [ 22 , 31 , 32 , 33 ]. Proximate analysis done by Henry et al. [ 33 ] showed that cow dung has higher ash content and less total solids compared to goat pellets. The above discoveries are in support of the result in Table 2 . Liman et al. [ 31 ] and Henry et al. [ 33 ] reported that poultry droppings have more ash content compared to cow dung which is contrary to the result of the analysis in this study (Table 2 ). Ofoefule and Uzodinma [ 22 ] and Liman et al. [ 31 ] reported that cow dung have more carbon contents and less nitrogen contents compared to chicken dropping which supports the findings in this study. It was widely reported that chicken droppings produced the highest volume of biogas followed by cow dung and then goat droppings, which they opined that it could be attributed to the nutrient contents in the substrate which are required by the organisms involved in methanogenesis [ 34 ]. It was also stated that the volume of biogas produced by cow dung is slightly higher than that produced by goat droppings [ 32 ]. The discovery of this research agrees with the report that biogas produced from chicken dropping is higher than those produced by cow dung and goat droppings, but disagrees with the above findings that the volume of biogas produced by cow dung is higher than the volume produced by goat droppings. Although, Liman et al. [ 31 ] in their work stated that the cumulative yield of biogas from cow dung is higher than that of poultry droppings which is different from the result of this study. Jayaraj et al. [ 35 ] reported that biogas production from food wastes was higher during initial days (first 10 days) and decreased gradually as the days passes over the 30-day retention period which corresponds with the findings on this work. Musa and Raji [ 34 ] observed that during biogas production from animal wastes over a three weeks retention period, goat droppings gave the highest biogas yield on the first week and the least biogas yield on the third week, cow dung gave the least biogas yield on the first week and the highest biogas yield on the third week, while, chicken droppings gave the highest biogas yield on the first week and the least yield on the second week. The above report of biogas yield with respect to retention period for goat droppings only agrees with the findings of this study. Liman et al. [ 31 ] in their work showed that cow dung gave the highest biogas yield between day 6 and day 15 of the retention period and poultry droppings gave the highest biogas yield between day 5 and day 12 of the retention period which agrees with the result of this work at the same retention period for cow dung only. Jayaraj et al. [ 35 ] and Lisowyj and Wright [ 6 ] opined that the pH of the substrate has a significant effect on biogas production, bacteria colonies because it affects the activity of bacteria to breakdown organic matter into biogas. Jayaraj et al. [ 35 ] further explained that a low pH in the digester inhibits the activity of microorganisms involved in the digestion process particularly methanogenic bacteria. It was reported that a digester with initial pH of 5, 6, 7, 8 and 9 stabilized (buffered) with 1N sodium bicarbonate solution, the percentage methane composition was highest in the digester with pH 7 followed by the digester with pH 8 [ 35 ]. Stoyancheva et al .[ 24 ] and Hassain et al. [ 36 ] stated that the appropriate pH level that helps bacteria to produce biogas is 6.4–7.6. The above reports and findings explain why the composition of biogas (in Tables 3 , 4 and 5 ) gave different proportions of biogas composition with the highest percentage of methane produced at pH 8. Liman et al. [ 31 ] and Atilade et al .[ 37 ] revealed in their works that chicken droppings have more methane content in their biogas composition than cow dung. Liman et al. [ 31 ] also showed that the pH of chicken droppings used for their biogas production is pH 7.65, while the pH of cow dung is pH 6.51, which explains why chicken droppings gave the best methane yield. Cu et al. [ 38 ] in their study observed that cow dung has the highest methane content followed by goat droppings and then chicken dropping. He explained that the reason for the relatively low methane concentration in chicken droppings is because of its high nitrogen content which is considered to be the main inhibiting factor. From the findings of this study, the nitrogen content of chicken droppings is high compared to that of cow dung and goat droppings which might have contributed to the low methane yield as opined by Cu et al. [ 38 ]. The data analysis (one-way ANOVA) for the biogas compositions of the three animal wastes shows that each of the results is not significant at p < 0.05. Conclusion The animal wastes that gave the highest biogas yield is chicken dropping followed by the co-digestion of chicken droppings and goat droppings, and co-digestion of cow dung and chicken droppings. It was also observed that at pH 8 with dark covering, all the animal wastes produced the highest percentage of methane gas. In addition, it was observed that the genera Burkholderia (Phylum Proteobacteria) is the genera with the highest mean relative abundance followed by Escherichia (Phylum Proteobacteria) and Caproicibacterium (Phylum Firmicutes). Thereby, making chicken dropping a good source for energy resource alternative, and or can be used to curb control for groundwater contamination. Declarations Acknowledgement The field work of this study is self funded from a Doctoral (Ph.D) research project. The authors express their profound gratitude to the editors and reviewers of this manuscript for their constructive comments to improve and enhance the quality of the manuscript. Conflict of Interest On behalf of all authors, the corresponding author states that there is no conflict of interest. Authors Contributions All the authors contributed to the conceptualization of the study and data collection. Preparation of the manuscript was done by Onyinyechukwu Goodluck Ugwuoke and Uche Ogugua Chukwura-Osoagba. The data collections were performed by Onyinyechukwu Goodluck Ugwuoke. The field work and data collections were supervised by Edna I. Chukwura. Funding: No funds, grants, or other support was received. Data availability (data transparency): Data generated in this study are provided within the manuscript and is available on demand from the corresponding author. Code availability (software application or custom code): Not applicable. Competing Interests: The authors have no relevant financial or non-financial interests to disclose. 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Comparison of the potentials of cow dung and poultry droppings as substrates for biogas production. Nuhu Bamalli Polytechnic J Sci Technol. 2023;1(3):187–98. Ngulde YM, Yerima I, Abubakar M. Evaluation of cow dung and goat pellets for production of biogas in university of maiduguri, north –eastern Nigeria. Afr J Environ Nat Sci Res. 2018;1(1):33–43. Henry VI, Ani OI, Iloabachie ICC, Chime AC. A comparative study of characterized cow dung and poultry droppings as a substrates in biogas digester. Int J Adv Eng Technol. 2018;2(2):22–6. Musa B, Raji HM. Quantitative and qualitative analysis of biogas produces from three organic wastes. Int J Renew Energy Res. 2016;6(1):299–305. Jayaraj S, Deepanraj B, Sivasubramanian V. (2014). Study on the effect of pH on biogas production from food waste by anaerobic digestion. The 9th International Green Energy Conference in Tianjin, China (IGEC-IX). pp. 799–805. Hussain AA, Johain JF, Fawziea MH. Effect of pH on biogas production during anaerobic digestion. J Univ Shanghai Sci Technol. 2021;23(8):224–31. Atilade AO, Onanuga OK, Coker JO. Comparative study of biogas generation from chicken waste, cow dung and pig waste using constructed plastic bio digesters. Int J Res Stud Biosci. 2014;2(10):47–51. Cu TTT, Nguyen TX, Triolo JM, Pedersen L, Le VD, Le PD, Sommer SG. Biogas Production from Vietnamese Animal Manure, Plant Residues and Organic Waste: Influence of Biomass Composition on Methane Yield. Asian Australasian J Anim Sci. 2015;28(2):280–9. Additional Declarations No competing interests reported. Supplementary Files APPENDIX.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 23 Oct, 2025 Reviews received at journal 03 Oct, 2025 Reviews received at journal 03 Oct, 2025 Reviews received at journal 29 Sep, 2025 Reviewers agreed at journal 24 Sep, 2025 Reviewers agreed at journal 22 Sep, 2025 Reviewers agreed at journal 21 Sep, 2025 Reviewers agreed at journal 21 Sep, 2025 Reviewers invited by journal 20 Sep, 2025 Editor invited by journal 13 Sep, 2025 Editor assigned by journal 31 Aug, 2025 Submission checks completed at journal 31 Aug, 2025 First submitted to journal 29 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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CHUKWURA-OSOAGBA","email":"","orcid":"","institution":"University of Calabar, Calabar, Cross River State, Nigeria","correspondingAuthor":false,"prefix":"","firstName":"Uche","middleName":"O.","lastName":"CHUKWURA-OSOAGBA","suffix":""},{"id":523067206,"identity":"5f50dc0b-2680-465c-9fad-44e2b5ee8668","order_by":2,"name":"Vivian N. ANAKWENZE","email":"","orcid":"","institution":"Nnamdi Azikiwe University, Awka, Anambra State, Nigeria.","correspondingAuthor":false,"prefix":"","firstName":"Vivian","middleName":"N.","lastName":"ANAKWENZE","suffix":""},{"id":523067207,"identity":"2e0fe315-a0dc-47b0-837b-1056d637d36e","order_by":3,"name":"Edna I. 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13:48:21","extension":"html","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":140472,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7491747/v1/1aca41fb105c07f43ad1df03.html"},{"id":92598593,"identity":"5618fb25-d877-4b08-89b9-5f2b29094d89","added_by":"auto","created_at":"2025-10-01 13:48:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":171777,"visible":true,"origin":"","legend":"\u003cp\u003eLocation Map of some parts of Anambra State showing the study area\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7491747/v1/be2238619d8450e48145bb55.png"},{"id":92598580,"identity":"a70c791e-e75a-4c93-9ba2-ec56db31b574","added_by":"auto","created_at":"2025-10-01 13:48:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":472789,"visible":true,"origin":"","legend":"\u003cp\u003ePhotographs showing sections of the animals and waste, and sample analysis in Awka, Anambra State\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7491747/v1/1e39d092da8c865e97be57a6.png"},{"id":92599922,"identity":"638a877c-2b9a-485c-a473-c7c1ffef0b80","added_by":"auto","created_at":"2025-10-01 13:56:20","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":13942,"visible":true,"origin":"","legend":"\u003cp\u003eTotal volumes of biogas produced from semi solid animal wastes over a period of 30 days\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7491747/v1/764406b280771a04f4869719.png"},{"id":92598586,"identity":"68e582b4-d151-4d92-9bc2-a222f74e7c63","added_by":"auto","created_at":"2025-10-01 13:48:21","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":35788,"visible":true,"origin":"","legend":"\u003cp\u003eVolumes of biogas produced from semi solid animal wastes at interval of five days\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7491747/v1/93e820804b12c6059415abb2.png"},{"id":92600086,"identity":"41de33a4-47e5-4787-afb0-936649b1cfe6","added_by":"auto","created_at":"2025-10-01 14:04:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1918252,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7491747/v1/9f1b7431-973d-4bd5-95aa-a442b08dc6bb.pdf"},{"id":92599960,"identity":"0e698898-8d61-4e30-85bf-566a4ef6869c","added_by":"auto","created_at":"2025-10-01 13:56:23","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15994,"visible":true,"origin":"","legend":"","description":"","filename":"APPENDIX.docx","url":"https://assets-eu.researchsquare.com/files/rs-7491747/v1/5c30e515707058480c2e62ca.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Comparative Study of Biogas produced from selected Animal Wastes at less-populated settlements in Awka North and South Local Government Area in Anambra State, South-East Nigeria.","fulltext":[{"header":"1.0 Introduction","content":"\u003cp\u003eThe accumulation and management of wastes in the environment has raised concerns because of the problems associated with waste disposal into the wider environment [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The conventional methods mostly used for the management and treatment of wastes have some demerits it poses to the environment [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. These methods of waste disposal cause environmental problems like uncontrolled release of methane and similar persistent organic pollutants (POPs) into the atmosphere, producing unpleasant odors and spread of pathogenic microorganisms [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe main aim of a waste management system is to potentially remove, or at least reduce to the minimum the negative effects on public health and/or the environment, it contributes to sustainability factors; and provides a net positive energy outcome [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Waste materials such as manure and various crop wastes are perfect candidates for energy production [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Organic wastes are reservoirs of carbon resources for energy production. The challenge in utilizing the economic and environmental viability of organic wastes is gaining an understanding of the waste production, characteristics, diversion and preprocessing methods, transport requirements, available conversion technologies and the overall energy production [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Considering various alternative energy sources, biomass has been an indispensable part of energy debate [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In fact, biomass plays a significant role as source of renewable energy, with huge potentials in the production of biofuels for transportation, electricity and heat [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eBiogas is obtained from the anaerobic breakdown of biomass by microorganisms. Biogas is a renewable energy source which has effective effects on nature [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The anaerobic digestion process goes through four stages, which are hydrolysis, acidogenesis, acetogenesis and methagenesis [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], and the organisms involved in each stage are referred to as hydrolyser, acidogen, acetogen and methanogen respectively [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Biogas consists mainly of methane and carbon dioxide together with other gases and vapours in small proportion such as hydrogen sulfide, hydrogen, water vapour, nitrogen and volatile organic compounds [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Therefore, the high concentration of methane makes biogas an attractive fuel and it is used in solving an emission problem since methane is several times more harmful than carbon dioxide [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Improper disposal of wastes and poor waste management has created environmental menace that is hazardous to both the environment and humans.\u003c/p\u003e\u003cp\u003eThe aim of this study is examine and characterize biogas produced from cow dung, goat droppings and chicken droppings in Awka North and South Local Government Area for energy production. The objectives of the study are to characterize the bacteria involved in biogas production; determine the volume of biogas produced and determine the compositions of biogas.\u003c/p\u003e"},{"header":"2.0 The Study Area","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Location, climate and geology of the study area\u003c/h2\u003e\u003cp\u003eThe study areas, Gariki, Amansea are located in Awka North Local Government Area, and Commissioners quarters in Awka South Local Government Area, are both in Anambra State, situated in the Anambra Basin of the Benue Trough in Nigeria. Generally, the Anambra Basin is referred to as Cretaceous/Tertiary basin, integration between the Benue Trough (Cretaceous) and Niger Delta basin (Tertiary) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The basin is bordered to the east by the Abakaliki anticlinorium, to the north and northwest by the basement rock and Benue hinge line respectively. Awka North lies between latitude 6\u003csup\u003eo\u003c/sup\u003e14\u0026rsquo;51\u0026rdquo;N and longitude 7\u003csup\u003eo\u003c/sup\u003e08\u0026rsquo;14\u0026rdquo;E, while Awka South lies between latitude 6\u003csup\u003eo\u003c/sup\u003e14\u0026rsquo;36\u0026rdquo;N and longitude 7\u003csup\u003eo\u003c/sup\u003e05\u0026rsquo;41\u0026rdquo;E in the Southeastern region of Nigeria (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). There are two main seasons influenced in the areas, namely the dry and dusty harmattan season, and the wet season. The dry and dusty harmattan is usually between Novembers to March, while the wet season is between Aprils to October yearly.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe Anambra Basin is dominantly filled with sediments (clastic) comprising of numerous lithostratigraphic units of thickness about 2500m, with several Formations and from upper Campanian to Recent in age [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The lithostratigraphic units consist of Nkporo Shale, Mamu, Ajali Sandstone, Nsukka, Imo Shale, Ameki, Nanka Sands, Ogwashi-Asaba, the Alluvial Plain Sands and Benin Formations. With the source of the sediments into the basin from the Cameroon massif and the Abakaliki synclinorium [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The study area, Awka North is predominantly underlain by Imo Shale, and characterized by undulating topography and distribution of the water drainage, vegetation, and formation of soils. The pattern of the drainage is referred as dendritic, consisting of regions with relatively homogeneous rock types, and relief of moderate to high degree [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e"},{"header":"3.0 Materials and Methods","content":"\u003cp\u003e\u003cem\u003e3.1 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Sample Collection\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAnimal wastes including fresh cow dung and goat droppings were collected from Gariki, Amansea, in Awka North, while fresh chicken droppings were collected from Iweama\u0026rsquo;s poultry farm at Commissioners quarters in Awka South LGA, Anambra state (Fig. 2). The samples were taken to Microbiology laboratory in sterile containers for analyses.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3.2 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Identification of Bacteria from Samples\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAfter the anaerobic digestion, the slurry was shaken gently and the supernatant taken for sequencing. The bacteria in the digested slurry were identified using targeted metagenomic sequencing on the 16S specific region from bacteria in the slurry.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3.3 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Digester design\u003c/p\u003e\n\u003cp\u003eThe bio-digester was designed using the method described by Tambuwal and Ogbiko [21]. One liter (1000cm\u003csup\u003e3\u003c/sup\u003e) conical flasks were used as the bio-digesters. The digester was covered with a stopper in such a way to make it airtight. A hole was bored on the stopper through which a polyvinylchloride pipe was connected to allow the passage of biogas. The biogas produced were passed through a polyvinylchloride pipe and collected in a polyvinylchloride ball (for qualitative analysis). Whereas, the gases that were not collected directly in a polyvinylchloride ball, were collected using inverted measuring cylinder (for quantitative analysis). The digesters were operated at ambient (room) temperature in the mesophilic range with a retention time of 30 days.\u003c/p\u003e\n\u003cp\u003e3.4 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Measurement and Analysis of biogas produced\u003c/p\u003e\n\u003cp\u003eThe volume of biogas produced was measured using the procedure of Tambuwal and Ogbiko [21]. The volume of biogas produced was measured daily by finding the volume of water displaced (downward displacement of water) by the gas in the inverted measuring cylinder that served as biogas collection system. The water used for trapping the biogas was acidified with 2% H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4.\u0026nbsp;\u003c/sub\u003eBiogas analysis was done using Gas Chromatography (GC) analysis.\u003c/p\u003e\n\u003cp\u003e3.5 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Slurry Preparation and loading of digester for semi-solid animal wastes (individually and when in combinations)\u003c/p\u003e\n\u003cp\u003eThe combination ratio of waste and water, with the combination ratio of the different wastes was done by slight modification of the method used by Ofoefule and Uzodinma [22]. The slurry was prepared by mixing the semi-solid animal wastes with water in the ratio of 1:2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBiogas produced by inverted glass measuring cylinder:\u003c/strong\u003e For the measurement of biogas produced using inverted glass measuring cylinder, the quantity of semi-solid animal waste used was 300g, while the volume of water was 600ml. Below are the formulations for the preparation of the animal slurry.\u003c/p\u003e\n\u003cp\u003ei. Cow dung = 300g\u003c/p\u003e\n\u003cp\u003eii. Chicken droppings = 300g\u003c/p\u003e\n\u003cp\u003eiii. Goat droppings = 300g\u003c/p\u003e\n\u003cp\u003eiv. Cow dung + Chicken droppings = 150g +150g\u003c/p\u003e\n\u003cp\u003ev. Cow dung + Goat droppings = 150g + 150g\u003c/p\u003e\n\u003cp\u003evi. Chicken droppings + Goat droppings = 150g + 150g\u003c/p\u003e\n\u003cp\u003evii. Cow dung\u003csub\u003e+\u0026nbsp;\u003c/sub\u003eChicken droppings + Goat droppings = 100g + 100g + 100g\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBiogas produced by GC analysis:\u003c/strong\u003e For the measurement of biogas produced using GC analysis, the quantity of semi-solid animal waste used was 300g, while the volume of water is 600mL. The digesters were prepared in three (3) groups, (a) those without dark covering, (b) those with dark covering, and (c) those with dark covering with its pH raised to pH 8. Below is the formulation for the preparation of the animal slurry.\u003c/p\u003e\n\u003cp\u003ei. Cow dung = 300g\u003c/p\u003e\n\u003cp\u003eii. Chicken droppings = 300g\u003c/p\u003e\n\u003cp\u003eiii. Goat dropping = 300g\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.6 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Data analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analysis was done using SPSS software version 20.0, and the data was analyzed. Data from gas chromatographic analysis for biogas produced from the chicken droppings, goat droppings and cow dung were compared using ANOVA. Tukey HSD comparison tests were used to evaluate the differences between and within treatments of various animal wastes, using a 5 % significance level (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e"},{"header":"4.0 Results and Discussion","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Bacteria involved in biogas production\u003c/h2\u003e\u003cp\u003eBacteria from 6 phyla, 20 genera, totaling 75 species were identified to be involved in the biogas production using targeted metagenomics sequencing on the 16S specific region from bacteria in the slurry (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The genera identified are Caproicibacterium, Burkholderia, Lactobacillus, Escherichia, Listeria, Veillonella, Clostridium, Bacillus, Pseudomonas, Cellulosilyticum, Prevotella, Romboutsia, Staphylococcus, Klebsiella, Enterococcus, Limosilactobacillus, Niameybacter, Salmonella, Caproiciproducens and Triponema. These genera belong to 6 phyla namely Proteobacteria, Bacteroidota, Bacillota, Actinomycetota, Spirochaetota and Firmicutes. The genera with the highest number of species are Clostridium, Lactobacillus and Limosilactobacillus with 13, 11 and 10 species respectively, whereas, Burkholderia, Veillonella, Pseudomonas, Cellulosilyticum, Prevotella, Romboutsia, Enterococcus and Caproiciproducens genera have one species each (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The metagenomic data shows that the phylum Firmicutes has the most bacteria diversity with the largest number of genera. The genera Burkholderia (Phylum Proteobacteria) is the genera with the highest mean relative abundance followed by Escherichia (Phylum Proteobacteria) and Caproicibacterium (Phylum Firmicutes).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eResult of targeted genomic sequencing (16S RNA sequencing)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhylum\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGenus\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSpecies\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFirmicutes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCaproicibacterium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eC. amylolyticum, C. sp900184925, C. sp902809935, C. sp004103755\u003c/em\u003e,\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProteobacteria\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBurkholderia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eB. lata\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFirmicutes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLactobacillus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eL. johnsonii, L. gallinarum, L. delbrueckii, L. crispatus, L. amylovorus, L. gigeriorum, L. kitasatonis, L. paragasseri, L. equicursoris, L. gasseri, L. prophage\u003c/em\u003e,\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProteobacteria\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEscherichia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eE. coli, E. fergusonii\u003c/em\u003e,\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFirmicutes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eListeria\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eL. monocytogenes, L. monocytogenes B, L. marthii\u003c/em\u003e,\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFirmicutes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVeillonella\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eV. magna\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFirmicutes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eClostridium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eC. cuniculi, C. luticellarii, C. tertium, C. tyrobutyricum, C. baratii, C. beijerinckii, C. butyricum, C. neonatale, C. nigeriense, C. paraputrificum, C. sartagoforme, C. sartagoforme A, C. saudiense, C. sp000753455, C. sp014836325, C. sp015555905, C. sp902809985\u003c/em\u003e,\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFirmicutes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBacillus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eB. spizizenii, B. vallismortis, B. intestinalis, B. nakamurai, B. sp010093085\u003c/em\u003e,\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProteobacteria\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePseudomonas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eP. aeruginosa\u003c/em\u003e,\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFirmicutes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCellulosilyticum\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eC. lentocellum\u003c/em\u003e,\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBacteroidota\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePrevotella\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eP. sp017347605\u003c/em\u003e,\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFirmicutes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRomboutsia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eR. ilealis\u003c/em\u003e,\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBacillota\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStaphylococcus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eS. aureus, S. phage\u003c/em\u003e,\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProteobacteria\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eKlebsiella\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eK. aerogenes, K. quasipneumoniae, K. variicola, K. africana, K. granulomatis, K. pneumoniae\u003c/em\u003e,\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBacillota\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEnterococcus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eE. faecalis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBacillota\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLimosilactobacillus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eL. antri, L. fermentum, L. ingluviei, L. mucosae, L. oris, L. pontis, L. reuteri, L. reuteri E, L. secaliphilus, L. vaginalis\u003c/em\u003e,\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eActinomycetota\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNiameybacter\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eN. massiliensis, N. stercoravium massiliensis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProteobacteria\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSalmonella\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eS. enterica, S. phage, S. virus\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFirmicutes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCaproiciproducens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eC. galactitolivorans\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpirochaetota\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTriponema\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eT. parvum, T. D sp900769975\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Physico-chemical properties of animal wastes\u003c/h2\u003e\u003cp\u003ePhysico chemical properties of cow dung, chicken droppings and goat droppings are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Cow dung has the highest moisture content (73.36%), followed by chicken droppings and goat having the least moisture. Goat droppings have the least ash content (7.51%) among the three animal wastes. Cow dung has the least fibre content (1.81%) and least total solids (26.65%) compared to chicken droppings and goat droppings. Chicken droppings have the highest percentage of nitrogen (4.03%) and cow dung has the highest percentage of volatile solids. Total organic carbon is highest in cow dung and lowest in goat droppings.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePhysico-chemical properties of semi-solid animal wastes (chicken droppings, cow dung and goat droppings).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS/No\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChicken dropping\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCow dung\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eGoat dropping\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMoisture content (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e59.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e73.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e57.32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAsh content (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFibre content (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.83\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal Solids (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e40.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e26.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e42.68\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal Nitrogen (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.47\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVolatile Solids (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal Organic Carbon (mg/kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.46\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCarbon - Nitrogen ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.42\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eVolume of biogas yield from semi solid animal wastes (cumulative volume and volumes at every 5-day interval)\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eCumulative volumes of biogas yield by animal wastes\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe total volumes of biogas produced by semi solid animal wastes individually and in combination are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Individually, chicken droppings produced the highest volume of biogas (5,472 cm\u003csup\u003e3\u003c/sup\u003e), followed by goat droppings (2,072 cm\u003csup\u003e3\u003c/sup\u003e), whereas, cow dung gave the least volume of biogas (1,546 cm\u003csup\u003e3\u003c/sup\u003e). When the animal wastes were combined, chicken droppings\u0026thinsp;+\u0026thinsp;goat droppings combination produced the highest volume (4,788 cm\u003csup\u003e3\u003c/sup\u003e) of biogas, while cow dung\u0026thinsp;+\u0026thinsp;goat droppings combination produced the lowest volume (1,253 cm\u003csup\u003e3\u003c/sup\u003e) of biogas (\u003cspan refid=\"Sec16\" class=\"InternalRef\"\u003eAppendix\u003c/span\u003e 1). Generally, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows that chicken droppings produced the highest volume of biogas, followed by the chicken droppings - goat droppings combination, while the cow dung - goat droppings combination produced the lowest volume of biogas.\u003c/p\u003e\u003cp\u003eV\u003cb\u003eolumes of biogas yields at interval of 5 days\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBiogas production by semi solid animal wastes were higher in the first 15 days of the retention period and lower in the second 15 days (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Generally, the volume of biogas produced decreased as the days passed. Cow dung has the highest biogas yield on the day 6 to day 10 retention period (\u003cspan refid=\"Sec16\" class=\"InternalRef\"\u003eAppendix\u003c/span\u003e 1). The volume of biogas produced from day 21 to day 25 retention period were higher than the volume produced from the previous 5 days for chicken droppings, goat droppings, cow dung - goat droppings combination, chicken droppings - goat droppings combination and cow dung - chicken droppings - goat dropping combination (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eComposition of biogas produced by chicken droppings\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBiogas from anaerobic digestion of chicken droppings from three different slurries (a: slurry at pH 6.8, without dark covering; b: slurry at pH 6.8, with dark covering; and c: slurry with pH raised to pH 8.0, with dark covering) were analyzed using gas chromatography (GC) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The slurry prepared at pH 8.0, produced the highest percentage of methane gas (CH\u003csub\u003e4\u003c/sub\u003e) (70.43%), whereas, the slurry without dark covering has the least percentage of CH\u003csub\u003e4\u003c/sub\u003e (60.30%) as indicated in their biogas compositions. The slurry that produced the highest percentage of carbon dioxide (CO\u003csub\u003e2\u003c/sub\u003e) (22.36%) is the slurry without dark covering, while the slurry with dark covering prepared at pH 6.8 has the least percentage of CO\u003csub\u003e2\u003c/sub\u003e (15.43%) in the biogas produced.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGas chromatographic analysis of biogas produced from Chicken droppings\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eConstituents\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e% Composition of biogas constituents\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA\u003c/p\u003e\u003cp\u003e(pH 6.8)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eB\u003c/p\u003e\u003cp\u003e(pH 6.8)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC\u003c/p\u003e\u003cp\u003e(pH 8.0)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEthanol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEthyl Acetate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.79\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHydrogen Sulphide\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMethane\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e60.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e68.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e70.43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcetic Acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcetonitrile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcetone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhenol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.57\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMethanol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eKeys:\u003c/p\u003e\u003cp\u003eA: the digester at pH 6.8 without dark covering\u003c/p\u003e\u003cp\u003eB: the digester at pH 6.8, with dark covering\u003c/p\u003e\u003cp\u003eC: the digester at pH 8.0, with dark covering\u003c/p\u003e\u003cp\u003e\u003cb\u003eComposition of biogas produced by goat droppings\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBiogas analyses from anaerobic digestion of three different slurries of goat droppings (a: slurry at pH 7.3, without dark covering; b: slurry at pH 7.3, with dark covering; and c: slurry with pH raised to pH 8.0, with dark covering) showed that slurry prepared at pH 8.0 gave the highest percentage of CH\u003csub\u003e4\u003c/sub\u003e (75.57%), while the slurry with dark covering at pH 7.3 has the least percentage of CH\u003csub\u003e4\u003c/sub\u003e (72.53%) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The GC results also showed that oxygen molecules (0.90%) were present in the biogas produced from the slurry with dark covering at pH 7.3. CO\u003csub\u003e2\u003c/sub\u003e was found to be lowest (21.28%) in the slurry prepared at pH 8.0 and highest (21.58%) in the slurry without dark covering at pH 7.3.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGas chromatographic analysis of biogas produced from Goat droppings\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eConstituents\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e% Composition of biogas constituents\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA\u003c/p\u003e\u003cp\u003e(pH 7.3)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eB\u003c/p\u003e\u003cp\u003e(pH 7.3)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC\u003c/p\u003e\u003cp\u003e(pH 8.0)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLactic Acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e21.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21.28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEthanol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.68\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMethane\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e75.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e72.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e75.57\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcetic Acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcetonitrile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcetone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOxygen\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBenzaldehyde\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMethanol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eKeys:\u003c/p\u003e\u003cp\u003eA: the digester at pH 7.3 without dark covering\u003c/p\u003e\u003cp\u003eB: the digester at pH 7.3, with dark covering\u003c/p\u003e\u003cp\u003eC: the digester at pH 8.0, with dark covering\u003c/p\u003e\u003cp\u003e\u003cb\u003eComposition of biogas produced by cow dung\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGC analyses of biogas produced from cow dung digestion (a: slurry at pH 6.9, without dark covering; b: slurry at pH 6.9, with dark covering; and c: slurry with pH raised to pH 8.0, with dark covering) showed that slurry with pH 8.0, with dark covering has the highest CH\u003csub\u003e4\u003c/sub\u003e concentration (76.96%), whereas, the slurry prepared at pH 6.9, with dark covering produced the least CH\u003csub\u003e4\u003c/sub\u003e concentration (61.99%) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The slurry prepared at pH 8.0, with dark covering has the least concentration of CO\u003csub\u003e2\u003c/sub\u003e (11.72%), whereas the slurry prepared at pH 6.9 with dark covering has the highest concentration of CO\u003csub\u003e2\u003c/sub\u003e (15.18%).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGas chromatographic analysis report of biogas produced from Cow dung\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eConstituents\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e% Composition of biogas constituents\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA\u003c/p\u003e\u003cp\u003e(pH 6.9)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eB\u003c/p\u003e\u003cp\u003e(pH 6.9)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC\u003c/p\u003e\u003cp\u003e(pH 8.0)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcetic acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.77\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhenol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.42\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcetone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEthanol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMethane\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e61.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e76.96\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChloroform\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.71\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMethanol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEthyl Acetate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eKeys:\u003c/p\u003e\u003cp\u003eA: the digester at pH 6.9 without dark covering\u003c/p\u003e\u003cp\u003eB: the digester at pH 6.9, with dark covering\u003c/p\u003e\u003cp\u003eC: the digester at pH 8.0, with dark covering\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Discussion\u003c/h2\u003e\u003cp\u003eProteobacteria, Firmicutes, Bacteroidetes and Actinobacteria have been reported as the four phyla that led bacterial domain in read relative abundance among biogas producing microbial composition [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The above findings are in line with the result of this study which shows that the bacteria involved in the anaerobic digestion of animal slurry are from the phyla Proteobacteria, Firmicutes and Bacteroidota (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). It has been shown that for treatment of solid feedstocks, the community is usually dominated by Firmicutes [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], while Stoyancheva \u003cem\u003eet al\u003c/em\u003e. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], also reported Firmicutes as a stable phylum during liquid manure and corn steep liquor treatment. The metagenomic data from this study confirmed that Firmicutes has a stable occurrence, but it also shows that Proteobacteria has more dominance in the digester.\u003c/p\u003e\u003cp\u003eStudies associated with the digestion of liquid feedstocks as sludge have reported Proteobacteria, Firmicutes and Bacteroidetes as dominant bacterial phyla, followed by Actinobacteria and Chloroflexi [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. This is in line with the result of this experiment which shows that the phylum Proteobacteria is the most abundant phylum compared to the other two phyla, which is also in agreement with the findings of Senes-Guerrero \u003cem\u003eet al\u003c/em\u003e. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], and Stoyancheva \u003cem\u003eet al\u003c/em\u003e. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMoisture contents of cow dung have been shown to be higher than those of chicken droppings and goat droppings [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Proximate analysis done by Henry \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] showed that cow dung has higher ash content and less total solids compared to goat pellets. The above discoveries are in support of the result in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Liman \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] and Henry \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] reported that poultry droppings have more ash content compared to cow dung which is contrary to the result of the analysis in this study (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Ofoefule and Uzodinma [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] and Liman \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] reported that cow dung have more carbon contents and less nitrogen contents compared to chicken dropping which supports the findings in this study.\u003c/p\u003e\u003cp\u003eIt was widely reported that chicken droppings produced the highest volume of biogas followed by cow dung and then goat droppings, which they opined that it could be attributed to the nutrient contents in the substrate which are required by the organisms involved in methanogenesis [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. It was also stated that the volume of biogas produced by cow dung is slightly higher than that produced by goat droppings [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The discovery of this research agrees with the report that biogas produced from chicken dropping is higher than those produced by cow dung and goat droppings, but disagrees with the above findings that the volume of biogas produced by cow dung is higher than the volume produced by goat droppings. Although, Liman \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] in their work stated that the cumulative yield of biogas from cow dung is higher than that of poultry droppings which is different from the result of this study.\u003c/p\u003e\u003cp\u003eJayaraj \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] reported that biogas production from food wastes was higher during initial days (first 10 days) and decreased gradually as the days passes over the 30-day retention period which corresponds with the findings on this work. Musa and Raji [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] observed that during biogas production from animal wastes over a three weeks retention period, goat droppings gave the highest biogas yield on the first week and the least biogas yield on the third week, cow dung gave the least biogas yield on the first week and the highest biogas yield on the third week, while, chicken droppings gave the highest biogas yield on the first week and the least yield on the second week. The above report of biogas yield with respect to retention period for goat droppings only agrees with the findings of this study. Liman \u003cem\u003eet al.\u003c/em\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] in their work showed that cow dung gave the highest biogas yield between day 6 and day 15 of the retention period and poultry droppings gave the highest biogas yield between day 5 and day 12 of the retention period which agrees with the result of this work at the same retention period for cow dung only.\u003c/p\u003e\u003cp\u003eJayaraj \u003cem\u003eet al.\u003c/em\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] and Lisowyj and Wright [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] opined that the pH of the substrate has a significant effect on biogas production, bacteria colonies because it affects the activity of bacteria to breakdown organic matter into biogas. Jayaraj \u003cem\u003eet al.\u003c/em\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] further explained that a low pH in the digester inhibits the activity of microorganisms involved in the digestion process particularly methanogenic bacteria. It was reported that a digester with initial pH of 5, 6, 7, 8 and 9 stabilized (buffered) with 1N sodium bicarbonate solution, the percentage methane composition was highest in the digester with pH 7 followed by the digester with pH 8 [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Stoyancheva \u003cem\u003eet al\u003c/em\u003e.[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] and Hassain \u003cem\u003eet al.\u003c/em\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] stated that the appropriate pH level that helps bacteria to produce biogas is 6.4\u0026ndash;7.6. The above reports and findings explain why the composition of biogas (in Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) gave different proportions of biogas composition with the highest percentage of methane produced at pH 8.\u003c/p\u003e\u003cp\u003eLiman \u003cem\u003eet al.\u003c/em\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] and Atilade \u003cem\u003eet al\u003c/em\u003e.[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] revealed in their works that chicken droppings have more methane content in their biogas composition than cow dung. Liman \u003cem\u003eet al.\u003c/em\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] also showed that the pH of chicken droppings used for their biogas production is pH 7.65, while the pH of cow dung is pH 6.51, which explains why chicken droppings gave the best methane yield. Cu \u003cem\u003eet al.\u003c/em\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] in their study observed that cow dung has the highest methane content followed by goat droppings and then chicken dropping. He explained that the reason for the relatively low methane concentration in chicken droppings is because of its high nitrogen content which is considered to be the main inhibiting factor. From the findings of this study, the nitrogen content of chicken droppings is high compared to that of cow dung and goat droppings which might have contributed to the low methane yield as opined by Cu \u003cem\u003eet al.\u003c/em\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe data analysis (one-way ANOVA) for the biogas compositions of the three animal wastes shows that each of the results is not significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe animal wastes that gave the highest biogas yield is chicken dropping followed by the co-digestion of chicken droppings and goat droppings, and co-digestion of cow dung and chicken droppings. It was also observed that at pH 8 with dark covering, all the animal wastes produced the highest percentage of methane gas. In addition, it was observed that the genera Burkholderia (Phylum Proteobacteria) is the genera with the highest mean relative abundance followed by Escherichia (Phylum Proteobacteria) and Caproicibacterium (Phylum Firmicutes). Thereby, making chicken dropping a good source for energy resource alternative, and or can be used to curb control for groundwater contamination.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe field work of this study is self funded from a Doctoral (Ph.D) research project. The authors express their profound gratitude to the editors and reviewers of this manuscript for their constructive comments to improve and enhance the quality of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOn behalf of all authors, the corresponding author states that there is no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the authors contributed to the conceptualization of the study and data collection. Preparation of the manuscript was done by Onyinyechukwu Goodluck Ugwuoke and Uche Ogugua Chukwura-Osoagba. The data collections were performed by Onyinyechukwu Goodluck Ugwuoke. The field work and data collections were supervised by Edna I. Chukwura. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eNo funds, grants, or other support was received.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e (data transparency): Data generated in this study are provided within the manuscript and is available on demand from the corresponding author.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e (software application or custom code): Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u0026nbsp;\u003c/strong\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval:\u0026nbsp;\u003c/strong\u003eNot Applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate:\u003c/strong\u003e The authors participated in the conceptualization of the study and data collection, and preparation of this manuscript\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e The authors state their consent for the preparation and publication of this manuscript\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLin CSK, Pfaltzgraff LA, Herrero-Davila L, Mubofu EB, Abderrahim S, Clark JH, Koutinas AA, Kopsahelis N, Stamatelatou K, Dickson F, Thankappan S, Mohamed Z, Brocklesby R, Lugue R. 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Asian Australasian J Anim Sci. 2015;28(2):280\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-environment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Environment](https://www.springer.com/44274/)","snPcode":"44274","submissionUrl":"https://submission.nature.com/new-submission/44274/3","title":"Discover Environment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Biogas, methane, bacteria, contaminant, animal waste, anaerobic digestion","lastPublishedDoi":"10.21203/rs.3.rs-7491747/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7491747/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eBiogas is a renewable source of energy generated from anaerobic digestion of biomass. A comparative analyses of biogas produced from anaerobic digestion of animal wastes (cow dung, goat droppings and chicken droppings) in Awka North and South Local Government Area, Nigeria were studied.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eLaboratory scale digesters (1000 cm\u003csup\u003e3\u003c/sup\u003e conical flasks) were used for the anaerobic digestion with retention period of 30 days and the experiment was carried out at room temperature. The biogas produced was trapped in inverted measuring glass cylinder to get the volume of gas produced and in poly vinyl chloride ball to hold the biogas for analysis of its constituent compositions. The animal wastes were mixed with water in the ratio of 1:2. Data were analyzed using ANOVA.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eTwenty bacteria genera belonging to six phyla including Firmicutes, Proteobacteria, Bacillota, Actinomycetota, Spirochaetota and Bacteroidota were identified to be involved in the anaerobic digestion process using 16S rRNA targeted genomic sequencing. The findings revealed the cumulative biogas yield by chicken droppings (CnD), cow dung (CwD), goat droppings (GtD), cow dung \u0026ndash; chicken droppings, cow dung \u0026ndash; goat droppings, chicken droppings \u0026ndash; goat droppings and cow dung \u0026ndash; chicken droppings \u0026ndash; goat droppings were 5472 cm\u003csup\u003e3\u003c/sup\u003e, 1546 cm\u003csup\u003e3\u003c/sup\u003e and 2072 cm\u003csup\u003e3,\u003c/sup\u003e 4607 cm\u003csup\u003e3\u003c/sup\u003e, 1253 cm\u003csup\u003e3\u003c/sup\u003e, 4788 cm\u003csup\u003e3\u003c/sup\u003e and 4111 cm\u003csup\u003e3\u003c/sup\u003e respectively. Biogas slurries for anaerobic digestion of animal wastes (cow dung, chicken droppings and goat droppings) were prepared in 3 designs (first digester without dark covering, second digester with dark covering and the third digester has dark covering with their pH raised to pH 8) with all the animal wastes producing highest percentage (CnD 70.43%, GtD 75.57%, CwD 76.96%) of methane (CH\u003csub\u003e4\u003c/sub\u003e) at the digesters with dark covering at pH 8. Statistical analysis on ANOVA reveals the biogas compositions of the animal wastes shows that they were not significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThe findings reveal the animal wastes with highest biogas yield were chicken dropping\u0026thinsp;\u0026gt;\u0026thinsp;co-digestion of chicken droppings and goats dropping\u0026thinsp;\u0026gt;\u0026thinsp;co-digestion of cow dropping and chicken droppings. These animal wastes produced highest percentage of methane gas at alkaline pH with dark covering. The chicken dropping with the highest biogas yield could be a good source for energy resource alternative, and or curb control for groundwater contamination, or used to reduce organic waste in landfills.\u003c/p\u003e","manuscriptTitle":"A Comparative Study of Biogas produced from selected Animal Wastes at less-populated settlements in Awka North and South Local Government Area in Anambra State, South-East Nigeria.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-01 13:48:15","doi":"10.21203/rs.3.rs-7491747/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-23T10:07:23+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-04T00:48:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-03T16:32:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-29T12:59:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"66294851323917983262917252209214573633","date":"2025-09-24T10:23:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"72851182595480549943677299632373705971","date":"2025-09-22T22:43:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"276287104140250777311876292865202348560","date":"2025-09-21T10:02:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"152193999397906055292226630560327923741","date":"2025-09-21T09:13:36+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-20T20:00:34+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-13T14:16:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-01T02:51:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-01T02:51:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Environment","date":"2025-08-29T22:28:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-environment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Environment](https://www.springer.com/44274/)","snPcode":"44274","submissionUrl":"https://submission.nature.com/new-submission/44274/3","title":"Discover Environment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f7fa4140-b7d8-4538-a244-91be848ea28a","owner":[],"postedDate":"October 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-12-29T05:38:57+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-01 13:48:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7491747","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7491747","identity":"rs-7491747","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}