Statement of Novelty

This study was carried out to explore the potential of producing biogas, bioenergy, bioelectricity and bio-fertilizer from cassava waste peels mixed with cow dung and cassava stem-based biochar using the integrated biorefinery approach unlike the single biorefinery approach. The work was designed to deepen our knowledge for the valorization of the huge cassava processing wastes that abound in Africa, especially Nigeria. It explored ways to address the paucity of data in the use of cassava stem-based biochar in biogas, bioenergy and biofertlizer production. The effects of the produced biofertilizers in the supplementation of garden loam soil for cultivation of Zea mays were also studied.

Introduction

In the tropics, cassava is regarded as the third most important source of calories, after rice and maize. About 550 million metric tons (MMT) of cassava are produced each year, resulting in 350 MMT of solid cassava wastes such as bagasse, peel, stem, rhizome, and leaves [53]. Cassava waste water contains as much suspended solids as up to 15,000 mg/L which are many occasions not treated before being released into the environment thus, contaminating nearby land [67] and water resources in the process. These wastes possess serious environmental threat due to acidification via hydrolysis of cassava cyanogenic glucoside, linamarin and lotaustralin (Methyl linamarin) which produces hydrogen cyanide (a compound toxic to household animals, fisheries and other organisms) [68]. According to [69] Adult female catfish, Clarias gariepinus was shown to have signs of gill and liver damage due to exposure to cassava waste water, with histopathological examination carried out on the gill, kidney and liver of fingerlings of the Nile Tilapia (Oreochromis noliticus) also revealing damages to these organs due exposure to cassava waste water. Omotosho and Amori [69] also reported anomalies in cell division process and chromosome aberration induction in Allium cepa root meristem due to cassava waste water heavy metal-cyanide interaction. These wastes can be employed for solid, liquid, and gaseous biofuels production [53]. According to Ekpo [18], one litre of cassava wastewater produces 16 ml and 9 ml of bioethanol and bio-methane respectively, while one kilogram of cassava peelings produces 226 ml of bioethanol and 118 ml of bio-methane. One kilogram of bagasse produces 20 ml of bioethanol and 10 ml of bio-methane. Okunade and Adekalu [, 71, 73] reported that cassava waste water which is five times denser than water contains alcohols, acids, and other organic compounds (Table 1). Whereas, Aripin et al. [, 72, 73] found that cassava solid waste was rich in holocellulose, cellulose, hemicellulose, lignin, and ash content with 1% of sodium hydroxide and hot water solubility (Table 1).

Table 1 Chemical composition of cassava waste water and oven-dried cassava peels
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The current over-dependence on crude oil for the synthesis of fuels and chemicals is not sustainable and poses a great challenge due to its negative impact on climate change and other adverse environmental effects [, 17, 35]. This has reawakened interest in the development of greener and cleaner alternatives to fossil fuels [, , 1, 12, 16]. Several researchers have proposed the concept of bioeconomy, which is centred on biomass sustainability, for the diversification of bio-based processes [8]. Many bacteria can catalyze biochemical reactions to produce bioelectricity via electron transfer, and this is what is now classified as Microbial fuel cells (MFCs).

In this bioelectrochemical process, electrons are released in the anode compartment (the negative terminal) via substrate oxidation by bacteria are transferred to the cathode compartment (the positive terminal) through a conductive material, whereas, in the cathode oxygen combines with the electrons causing the protons to diffuse through a proton exchange membrane [65].

Lignocellulosic materials from agricultural wastes are abundant and easily accessible naturally. Thus, they are sustainable bioenergy sources. Anaerobic digestion (AD) for the efficient use of lignocellulosic materials for the production of biogas has been studied extensively [5]. Cassava food crop has been used effectively as raw material for agro-based industries in the production of starch, bioethanol and other bio-based products. Huge quantities of wastes, that are abundant in organic matter and suspended solids, are generated from cassava-based industries. However, these generated wastes constitute weighty environmental concerns. Their multiple biochemical constitutions, as well as appreciable organic contents, avail them of the potential for bioconversion into value-added products via biorefinery, thus, providing environmental and economic sustainability to cassava processing industries [, 18, 64]. To improve the production of biogas from food wastes, various steps such as boosting operational parameters, additives application, and recirculation of digestate, regular feeding, and feedstock pretreatments can be explored [36]. Biochar has proven to be a viable additive in achieving steady and effective methane production during AD amongst other optimization procedures [51]. Biochar, as carbonaceous material, can be produced from several organic waste feedstocks such as municipal sewage sludge and agricultural wastes [56]. This could be done through the combustion of plant and animal materials in oxygen-limiting condition at particular temperatures. This combustion results in increased absorbing capacity for chemicals and compounds onto the surfaces of the biochar [20]. Biochar has been reported to be an extremely versatile material, economical and reliable additive in AD, which aids in microbial enrichment and biogas production boost [, 14, 32]. It is imperative to note that when biochar-amended digestate is augmented with nutrients such as phosphorus, potassium and nitrogen, it subsequently develops huge capability for soil applications [50] and can, thus, be used to improve the soil ecosystem [20].

In most previous studies, the valorization of cassava peels to biofuels and biofertilizers was considered only a single refinery process, thus discarding the useful biomass that could serve as raw materials for further successive biorefinery operations. This study, therefore, employed the integrated biorefinery approach to produce biofuels (biogas and bioelectricity) and bio-fertilizer from cassava peels, cow dung and cassava stem biochar.

Materials and Methods

Waste Collection, Preparation and Charring

Fresh samples of cassava solid (cassava peels (CPL), Cassava stems (CS), and cassava mill effluent (CME) wastes were collected from a local cassava processing factory located in Agbani community while the cow dung used as inoculum was collected from Ikpa market abattoir, all located in Nsukka Local Government Area of Enugu State, Nigeria. The CS and CPL were washed three times in running tap water to remove impurities. The washed CS and CPL were mechanically crushed in bits with a mechanical grinding machine. Thereafter, the crushed CPL was stored in plastic bags prior to use, while the CS was pyrolyzed at 400 °C for 1 h in the absence of oxygen and stored in an airtight bag after cooling prior to use. The CME was sieved with a 600 µm size mesh and thereafter, the filtrate was collected with a clean plastic container and stored prior to use.

Bioreactor Setup for Anaerobic Digestion

Four pilot scale 5 L (L) capacity bioreactors were constructed using 5L plastic containers with airtight lids. For each bioreactor, two graphite electrodes (1.5 cm diameter and 16 cm long) were inserted through two openings on the lid into the anode and cathode chambers of the bioreactor. Thereafter, the electrodes from each chamber were connected using a number 4 copper wires. Three (3) other openings were made on the lid of the cathode chamber, where a thermometer (for temperature reading), a rubber tubing that extends to the base of the chamber with a tight clip to maintain anaerobiosis (for sample collection), and another rubber tubing just above the liquid level (for gas collection) were inserted. The gas collection was by upward delivery and downward displacement of water (Fig. 1). The four bioreactors containing varying doses of biochar (0 g, 10 g, 20 g and 30 g) in the anode chamber were each charged with 800 g of crushed CPL, 200 g of cow dung and 3 L of CME and mixed together to make a 4 L mixture. The controls were bioreactors containing 4 L of water alone in place of the CPL, Cow dung and CME mixture. The bioreactors were then properly sealed using Epoxy glue to prevent air influx. Anaerobic digestion was carried out for 15 days. The experiments were carried out in duplicates. The volume of biogas produced was measured every 24 h by calculating the volume of water displaced into the collection bottle. The power outputs (current and voltage) were recorded every 24 h using a digital multimeter (model NENG™ Q1). The slurries (mixtures) were sampled before and after the 15-day digestion to determine the total solids (TS), volatile solid (VS), chemical oxygen demand (COD), organic carbon (OC), nitrogen content and pH values.

Plate 1
figure 1

Molecular identification of the phosphate and potassium solubilizing bacteria and fungi using 16SrRNA and ITS respectively

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Fig. 1
figure 1

Schematic diagram and picture of the Bioreactor (MFC system) used in this study

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Determination of Bioenergy Generation and Parameter Change in the MFC

Current and Voltage Generation Determination

Current (I) and voltage (V) measurements were done using an auto-range digital multimeter (model NENG™ Q1). The readings were taken and recorded by connecting the multimeter to the anode and cathode terminals of each digester. Power (W) was calculated using formula:

$$P = IV,$$

where I and V represents current and voltage respectively.

Determination of Power Density

The quantity of power produced per unit area is known as power density. The anode surface area was utilized to determine power density since all biological reactions, including degradation and anion generation, take place at the anode [31]. The power density (P) based on the surface area of the graphite rod anode (m2) was determined according to the formula of Momoh and Naeyor [37].

$${\text{Power}}{\mkern 1mu} {\text{density}}\left( P \right) = \frac{I \times V}{A}$$

where I: current (in mA); V: voltage (V); and A: surface area (m2).

Determination of Current Density

The quantity of current flowing through per unit area is known as the current density. The anode was also utilized because it is where all biological actions occur [39]. The current density (mA/m2) was determined using the formula:

$$J = \frac{I}{A}$$

where J is current density (mA/m2), A is area of the anode (m2) and I is flowing current (mA).

Determination of COD Removal Efficiency

The efficiency of COD removal was calculated using the formula of Kumar et al. (2020):

$${\text{COD }}\,{\text{removal }}\,{\text{efficiency}} \left( \% \right) = \frac{Ci - Cf}{{Ci}} \times 100$$

where Ci is initial value of COD and Cf is the final value of the COD

Parameters Change

The changes in the different physicochemical parameters (COD, TS, VS, pH, OC and NC) were calculated using the formula:

$${\text{Change}}\,{\text{ in }}\,{\text{parameter}} = \frac{{{\text{Initial }}\,{\text{value}} - {\text{Final}}\,{\text{ value}}}}{{{\text{Initial}}\,{\text{ value}}}} \times 100$$

Microbial Isolation, Screening and Digestate Curing

Composite soil samples were obtained using a sterile spatula from 4 cm depths at different spots at the cassava processing factory dumpsite. The samples were transported to the laboratory in sterile plastic containers for storage at 4 °C prior to use. Thereafter, bacteria and fungi were isolated from the soil samples by inoculating 1.0 g of each soil sample into different test tubes containing 9 ml of sterile distilled water. Six-fold serial dilution was done, after which a loopful of the diluted sample was used to inoculate freshly prepared nutrient agar (NA: 2.0 g/L yeast extract, 5.0 g/L sodium chloride, 15 g/L agar) and Sabouraud dextrose agar (SDA: 40 g/L dextrose, 10 g/L peptone, and 20 g/L agar) respectively using standard protocol [66]. The NA plates were incubated at 30 °C for 24 to 48 h, while the SDA plates were incubated at 30 °C for 3 to 5 days. Morphologically distinct colonies were purified by step-wise sub-culturing onto the same freshly prepared medium plate. The pure isolates were stored in slants at 4 °C for further use.

Qualitative Isolate Screening for Phosphate and Potassium Solubilizers

For Phosphate solubilization, the Pikovskaya medium used was prepared by dissolving 0.5 g (NH4)2SO4, 0.1 g MgSO4·7H2O, 0.02 g NaCl, 0.003 g FeSO4·7H2O, 0.003 g MnSO4·H2O, 0.02 g KCl, 5 g Ca3 (PO4)2, 0.5 g yeast extract, 10.0 g glucose and 15.0 g agar in 1 L of distilled water. The medium was thereafter autoclaved at 121 °C for 15 min and 20 ml of each of the sterilized molten agar media was poured into different sterile petri dishes and allowed to solidify before inoculation. Spot inoculation of bacterial and fungal isolates was made onto the respective petri dishes and incubated at 30 °C for 72 h. This was done in triplicates. Uninoculated Pikovskaya medium plate served as the control. The formation of clear zones around a colony was indicative of phosphate solubilization potential by the isolate. The solubilization index for the isolates was calculated using the formula [7].

$$Phosphate \,solubilization\, index \left( {PSI} \right) = \frac{{C \left( {mm} \right) + Z\left( {mm} \right)}}{{C \left( {mm} \right)}}$$

C = Colony diameter in millimeter, Z = Halo zone diameter in millimeter.

For Potassium solubilization, the Aleksandrov medium containing (g/L) 3.0 g potassium aluminum silicate, 0.5 g MgSO4.7H2O, 0.1 g CaCO3, 5.0 g glucose, 0.006 g FeCl3, 2.0 g Ca3(PO4)2, 20.0 g agar in 1 L of distilled water was used [23]. The medium, after sterilization, was transferred into sterile plates to solidify at room temperature. Screening for potassium solubilization was carried out according to the method described by Hu [23]. The isolates (fungal and bacterial) were spot inoculated onto prepared sterile petri dishes in triplicates and incubated at 30 °C for 72 h. The formation of a clear zone around an isolate was indicative of potassium solubilization potential of the isolate. The solubilization indices were determined using the formula:

$$Potassium\, solubilization\, index \left( {KSI} \right) = \frac{{C \left( {mm} \right) + Z\left( {mm} \right)}}{{C \left( {mm} \right)}}$$

where C = Colony diameter in millimeter, Z = Halo zone diameter in millimeter.

The isolates with significant solubilization indices for both phosphorous and potassium were selected and stored at 4 °C for further use.

Digestate Curing for Biofertilizer Formulation and Agronomic Test

Bacterial isolates used for digestate curing were standardized according to the method described by Elias et al. [19]. About 10 loop full of 24 h freshly prepared cultures of the selected phosphate and potassium bacterial solubilizers were inoculated into 50 ml nutrient broths, and incubated at 30 °C for 24 h at 120 rpm in an IKA KS 4000i rotary shaker. Thereafter, the bacterial cells were harvested by centrifuging at 5000 rpm for 10 min using a Hettich Rotoflix 11 centrifuge. The supernatant was discarded, and the cells were re-washed and vortexed thrice with normal saline. After washing, the cells were resuspended in normal saline. For the selected fungi, fresh spores of the fungal phosphate and potassium solubilizers were grown on SDA medium at 30 °C for 5 days. Using 5 ml of sterile 0.2% Tween-20 with gentle scraping, the spores were put in suspension and counted using a Neubauer counting chamber. One millilitre (1 ml) of the bacterial suspension (containing 106 CFU of each bacterial isolate) or fungal suspension (containing 108 spores of each fungal isolate) was used to cure 10 g of the digestate for 21 days at 30 °C in an open aluminum pan before use in biofertilizer formulation. The biofertilizer formulation was done according to the method described by Ogbo [41].

Five hundred grams (500 g) of screened loam soil (without debris, broken bottles and stones) was collected from the University of Nigeria Agriculture farm and moistened slightly with water at field capacity before it was packaged into polyethene bags and sterilized thrice at 120 °C for 50 min at 48 h intervals. The sterile loam soil in the polyethene bags was then mixed with the biofertilizers in the ratio of 10:1 and grouped as follows: Pot1-B5CPL; Pot2- B7CPL; Pot3-B24CPL; Pot4-F1CPL; Pot5-F3CPL; Pot6-F15CPL; Pot7- control (un-inoculated). Each group was done in triplicate and seeded with three seeds of maize (Zea mays). The seeded pots were frequently watered uniformly in a greenhouse (tunnel) for 20 days. The germination counts were taken at weekly intervals up to the third week to determine the germination indices.

Measurement of Germination Indices

The Germination percentage (GP) and germination rate indices (GRI) were determined using the formula of Shinde et al. [52]:

$${\text{Germination}}\,{\text{ percentage}} \left( {{\text{GP}}} \right) = \frac{{{\text{germinated }}\,{\text{seeds}}}}{{{\text{total}}\,{\text{ no}}\,{\text{ of}}\,{\text{ seeds}}\,{\text{ planted}}}} \times 100$$
$${\text{Germination }}\,{\text{rate}}\,{\text{ index }}\left( {{\text{GRI}}} \right){ = }\frac{{{\text{No}}\,{\text{ of}}\,{\text{ seeds}}\,{\text{ germinated}}\,{\text{ on}}\,{\text{ 20th}}\,{\text{ day}}}}{{{\text{day}}\,{\text{ of}}\,{\text{ germination}}}}$$

Bacterial Community Analysis

The liquid digestate samples at the end of the 15 day digestion in Sect. "Bioreactor Setup for Anaerobic Digestion" were collected and examined for the bacterial community composition. The bacterial communities attached to the anode chamber were analyzed by high-throughput metagenomic sequencing using the 16S rRNA. Digestate samples taken at the 15th day for analysis of bacterial and methanogenic communities were centrifuged at 12,000×g for 15 min. Thereafter, 0.4 g of the residue was used to extract genomic DNA of microbial communities using DNA isolation kits (Mo Bio Laboratories, Inc. Carlsbad, USA). The DNA quality was confirmed using a 1.0% agarose gel electrophoresis, and measured at 260 and 280 nm wavelengths. Amplifications of the V3–V4 region of 16S rRNA gene in bacterial and methanogenic communities were performed via the polymerase chain reaction (PCR). A set of primers ARC787F (5′-ATTAGATACCCSBGTAGTCC-3′) and ARC1059R (5′-GCCATGCACCWCCTCT-3′) were used to target methanogenic communities, while another set of primers 1369F (5′-CGGTGAATACGTTCYCGG-3′) and 1492R (5′-GGWTACCTTGTTACGACTT-3′) were used to target bacterial communities. Subsequently, sequencing of the DNA samples was conducted by Illumina Hiseq 2000 pyrosequencing platform. The phylogenetic relationship was analysed using Graph Pad Prism (version 7.04) and Microsoft excel (2013 version).

Statistical Analysis

All the data obtained were statistically analyzed using one-way analysis of variance (ANOVA) and Tukey’s multiple comparison tests. The correlation regression analysis was also done to ascertain the effect of biochar dosage on biogas and bioelectricity production as well as the germination index potentials of the biofertilizers at p < 0.05. Evaluations of all graphs in this study were made using GraphPad Prism 7.04.

Results and Discussion

The Effect of Different Doses of Biochar on Current and Voltage Generation

Maximum current and voltage were elicited at different times by different biochar concentrations (Fig. 2). The values of the current and voltage produced by each biochar concentration were significantly higher than the control and increased progressively as the biochar concentrations were increased from 10.0 to 30.0 g. The addition of biochar caused a surge in the power generation in all the digesters with biochar up to the 168th h anaerobic digestion. Thereafter, there was a steady decline in power up to the 360th h. This could be attributed to the gradual depletion of the readily available nutrients and shift in the microbial community present in the batch reactors. On initiation of the AD, the power output was extremely minimal probably because the microbial biofilm had not yet been established on the surface of the anode [22]. Biochar dose of 30 g gave the highest power density (94.33 ± 2.99 mW/m2) which was about 7.36-fold higher than the value of the control (12.81 ± 2.1 mW/m2) (Fig. 3). The increased power density observed with increased biochar concentration suggests that the biochar used in this study may be a good catalyst for microbial fuel cells probably due to its excellent electrocatalytic activity in promoting oxygen reduction reaction (ORR) [62]. ORR is currently reported as a major barrier in up-scaling the generation of bioelectricity in microbial fuel cell [, 27, 28]. The increased bioelectricity generation at higher doses of biochar in this study indicates the possibility of overcoming this limitation in up-scaling bioelectricity generation by using biochar. Furthermore, the use of waste-derived biochar in place of a catalyst to improve bioelectricity generation from CPL is considered cost efficient when compared to carbon, iron and nitrogen-based functionalized electrodes or cathode catalysts [62] at the commercial level for wastewater treatment and generation of power for low-energy devices. It is a welcome development as reported by Chakraborty et al. [11]. Interestingly, biochar dosing in this study demonstrated triple positive effects on commercial values. For instance, it enhanced waste treatment and electricity generation as reported by Hassan et al., [22], and simultaneous biogas production probably via direct interspecies electron transport (DIET) as observed by Onwosi et al. [43].

Fig. 2
figure 2

Effect of biochar doses on current and voltage generated within the 360 h in the MFCs. a 0 g biochar, b 10 g biochar, c 20 g biochar, d 30 g biochar

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Fig. 3
figure 3

Effect of biochar doses on maximum power density and current density generated within 360 h in the MFCs. PD power density, CD current density

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Effect of Different Doses of Biochar on Biogas Production

The 5-L bioreactor design and set-up for anaerobic digestion are shown in Fig. 1. Biogas production commenced within 24 h of the digestion for all the biochar concentrations. However, the days of optimum production varied at different concentrations of biochar (Fig. 4). This appears to be biochar concentration dependent as the cumulative volume of biogas produced (79.8 ± 0.14 ml) with addition of 30.0 g biochar was expressively higher than the values generated by other concentrations, while the control (without biochar) yielded the least value (Fig. 5). The decline in biogas production over time could be linked to the gradual exhaustion of the readily accessible nutrients for the microorganisms to metabolize in the biodigester. Several workers have reported increased biogas production at increased biochar concentrations [, , 34, 56, 63]. However, in the present study, concentrations above 30.0 g of biochar were not tested. The commencement of biogas production within 24 h of charging the digesters is in agreement with the report of Saravanan and Manikandan [49] on water hyacinth systems. On the contrary, Dahunsi and Oranusi [15], in their work, reported that biogas generation commenced on the ninth day. This may be due to different substrates or biochar sources used in the various studies. According to Pan et al. [45], some important functions of biochar include enhancing and balancing the hydrolysis, acidogenesis-acetogenesis, and methanogenesis stages of biogas production as well as relieving inhibitor stress, support for microbial colonies, and a reinforcer for buffer ability. Being a carbonaceous adsorbent material, biochar has the potential to sorb chemicals onto its surface [20]. It is envisaged that cumulative biogas production from all the digesters would increase over time. Thus, the increased cumulative production of biogas from all digesters during anaerobic digestion was expected, considering that the amendment of the cassava processing wastes CPL with cow dung inoculum introduced a consortium of microorganisms. These microorganisms were synergistically availed of essential nutrients for optimum activities throughout the anaerobic digestion. Digesters with different doses of biochar yielded significant biogas when compared with digesters without biochar (control). This agrees with Luo et al. [33], who reported that the addition of biochar (10 g/L) to mesophilic anaerobic digesters decreased the methanogenic lag phase and upstretched the maximum methane production rate when compared with the controls without biochar. Biochar undoubtedly has proven effective as an additive that enhances methane production via anaerobic digestion [51]. In this study, the optimum biochar dosage range was ascertained to be 20 g to 30 g per 4-L working volume for CPL.

Fig. 4
figure 4

Effect of different doses of biochar on daily production of biogas from CPL slurry

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Fig. 5
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Cumulative volume of biogas at different percentages of biochar for cassava peels (CPL)

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Physicochemical Parameters of the Digestate

There were progressive reductions in the COD, OC and VS as the dose of biochar increased in all the setups except in the digester with 10 g biochar, which had the highest COD reduction (81.0%) after digestion (Table 2). This was consistent with the feasibility study of Rashid et al. [47] on paraboloid graphite-based microbial fuel cells for bioelectrogenesis and pharmaceutical wastewater treatment, which showed a considerable COD reduction of 80.55%. However, in this study, the percentage reduction of the COD was 65.3% for 30 g biochar addition, 58.5% for 20 g biochar addition and 60.0% for no biochar addition (Control).

Table 2 Changes in physicochemical parameters after anaerobic digestion
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Reductions of 60.6, 54.4, 53.5, and 51.5% were observed in the organic carbon (OC) after digestion for 0, 10, 20 and 30 g biochar additions respectively. Organic carbon reductions of 69.21% and 74.3% have been reported by Kumar et al., [25] and Owamah et al. [44] respectively. Though their rates of reduction were much higher than the rate in the study, this could be linked to the HRT of their respective studies. The VS percentage change results after digestion showed that CPL with no biochar addition had the highest reduction of 69.5%, followed by 10 g biochar addition (59.5%), 20 g biochar addition (49.7%) and 30 g biochar addition (43.6%). The highest reduction in VS was congruent with the report of Kumar et al. [25] which showed a reduction of 68.69% in volatile solid. The observed reductions in feedstock before digestion may be attributed to the biodegradation of the organic matter present in the substrate due to the actions of mesophilic microorganisms.

It was observed that before the digestion, the addition of biochar increased the concentration of TS, NC, and pH in all the CPL digesters as shown in Table 2. However, there was a corresponding reduction of TS, NC, COD, OC, and NC after digestion at different biochar doses. The percentage change increase for TS was 47.5, 50.0, 45.1 and 56.4% for 0, 10, 20 and 30 g biochar addition respectively. Owamah et al. [44], noted an upsurge of 12.4% in TS after the co-digestion of food wastes and human excreta for biofertilizers production. There were 52.1, 52.2, 52.9 and 60.2% NC increases in the digesters with 0, 10, 20 and 30 g biochar additions respectively.

Throughout the duration of the anaerobic digestion, the pH values fluctuated between 6.25 and 7.15 and this aligns with the report of Shen et al. [51] which showed that pH fluctuated between 6.6 and 7.4 throughout the anaerobic digestion period. For temperature, it was observed to be between 25 and 360C all through the period of the anaerobic digestion process. This agrees with Giwa et al. [21] who studied the performance of anaerobic digestion in reactors with biochar and noted that as biochar addition improved, there was higher methane yield and reactor stability under mesophilic temperatures. The temperatures were between 26 and 36 °C. This also is in accord with the study of Oladejo et al. [42].

The C/N ratio was within the normal range both before and after digestion. This could be ascribed to the substrate which served as both carbon and nitrogen source. Also, the metabolic activities of the diverse microorganisms in the bioreactors could have played a role.

Solubilization Indices and Identification of Microbial Isolates

A total of 55 strains (30 bacterial and 25 fungal) were isolated from the soil samples. Based on the screening potentials on agar plates (Pikovskaya and Alexandrov respectively), nine out of the 30 bacterial isolates (30%) and seven out of the 25 fungal isolates (28%) had halo zones (Fig. 6). However, three each of the bacterial (b5, B7 and B24) and fungal (F1, F3 and F15) isolates were selected based on their high solubilization indices (SI). The selected bacterial and fungal strains had the potential for simultaneous solubilization of both phosphate and potassium as suggested in the study of Muthukumarasamy et al. [38] that urged farmers to employ a single microbe for microbial supplementation of N, P and K rather than a consortium of bacteria in order not to jeopardize the compatibility between various microbes.

Fig. 6
figure 6

Phosphate (A and B) and potassium (C and D) solubilizers for bacterial (B’s) and fungal (F’s) isolates

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The selected bacterial isolates (B5, B7, and B24) had the best solubilization indices of 6.55 ± 0.36 mm, 5.47 ± 0.56 mm, 6.07 ± 1.02 mm and 5.78 ± 0.44 mm, 7.16 ± 1.62 mm, 5.41 ± 0.17 mm for phosphorus and potassium respectively. Again, the selected fungal isolates (F1, F3 and F15) had the best solubilization indices of 6.08 ± 0.42 mm, 5.86 ± 0.32 mm, 5.51 ± 0.17 mm and 5.41 ± 0.66 mm, 7.99 ± 0.44 mm, 5.04 ± 0.25 mm for phosphate and potassium respectively. The phosphate and potassium solubilization indices for both bacterial and fungal isolates in this study are significantly higher than the values of 1.63–3.29 mm reported by Alam et al. [3]. However, findings from this study are in agreement with the range of values reported by Batool and Iqbal [7]. In addition, Kumari et al. [26] reported index values in the range of 8 to 13 mm for phosphate solubilization and 9.4 to 15 mm for potassium solubilization. Also, Aliyat [4] reported a bacterial solubilization index of 4.79 mm. The observed disparities in the ranges of the solubilization indices could be a pointer that different strains of microorganisms have different capacities or potentials for solubilization. Furthermore, different environmental factors, such as temperature and pH, can either promote or retard the solubilization processes.

The six (6) selected microbial strains used in this study (Plate 1) were identified using 16S rRNA gene sequence comparisons. The B5 isolate is Stenotrophomonas rhizophila strain 16YSM- P 39 16S, B7 is Alcaligenes faecalis strain C1FT MFB 14,415 (VRL 20) 16S, B24 is Alcaligenes faecalis strain BT10 16S, F1 is Aspergillus aculeatus strain JO6 18S, F3 is Aspergillus aculeatus strain CLSS 18S and F15 is Aspergillus alliaceus strain IHEM 22,316.

Formulation of Biofertilizers and Agronomic test

Phosphate and potassium solubilizers caused substantial increases (p < 0.05) in seed germination indices analysed (Fig. 7). The Zea mays planted in the soil inoculated with the selected bacterial strains had Zea mays had higher total lengths than Zea mays planted in the soil inoculated with selected fungal strains. When total mean lengths elicited by the biofertilizers were compared with the controls, there were significant increases in pot3-B24CPL (88.7 ± 13 mm), pot2-B7CPL (76 ± 15 mm), pot1-B5CPL (74.6 ± 15 mm), pot5-F3CPL (70.3 ± 17 mm), pot6-F15CPL (65.8 ± 8 mm) and pot4-F1CPL (58.3 ± 4 mm), while the control (uninoculated) had value of 40.55 ± 14 mm. The B24CPL had the highest total length of 88.7 ± 13 mm with a corresponding root length of 24.5 ± 1.2 mm, while F1CPL had the least total length of 58.3 ± 4 mm with a corresponding root length of 12.3 ± 5.5 mm amongst the planted seeds. These results agree with the report of Shinde et al. [52] and support the suggestion that the selected bacterial and fungal isolates selected are good phosphate and potassium solubilizers. Thus, they are good biofertilizers with potentials to improve maize crop production. In addition to improving crop production, the application of biofertilizers has the dual advantage of environmental sustainability and bioeconomy as against the application of chemical fertilizer [, 2, 7]. Table 3 shows the standard specification of biochemical properties of biofertilizer as adapted from Abdullahi et al. [70]. Furthermore, the biofertilizers have potential for commercialization, which is good for bioeconomy although the genetic stability should be verified. Several other authors have reported on the use of biofertilizers for the cultivation of maize seedlings [, 24, 48]. Table 4 shows effects of biofertilizers on Zea mays germination from this study.

Fig. 7
figure 7

Effect of different biofertilizer treatments on germination indices (A Root length; B Total length) of potted maize crop CPL (cassava peels)

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Table 3 Standard specifications of biofertilizer
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Table 4 Effects of biofertilizers on Zea mays germination
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Community Analysis of the Microbes

The bacterial and archaeal populations were assessed using Illumina sequencing of 16S rRNA gene amplicons. The sludge/digestate samples were collected at the end of the bioelectricity generation and biogas production phase for community analysis of the microbes. The preferred sequencing primer group for the 16S pyrosequencing allowed direct confirmation to be established for the classification of the microbial communities in the biodigester and also captured their relative abundance. As shown in Fig. 8, the top 5 dominant bacterial phyla in the digesters amended with biochar were Firmicutes (73.99%), Bacteroides (17.90%) Actinobacteria (5.18%), unclassified at the phylum level (2.67%) and Proteobacteria (0.08%), covering 99.82% of total abundance.

Fig. 8
figure 8

Top classification of the microbes in CPL digestates at phylum levels

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The dominant bacterial community in this study was consistent with the work of Sun et al. [55] who reported that acetic acid and hydrogen generation were carried out by Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria. They were also found to dominate in the anaerobic digester of beer lees [55]. Firmicutes have the potential for secreting varieties of extracellular enzymes, which contain cellulases, proteases and other enzymes that facilitate complex macromolecules hydrolysis [13]. The dominant phyla in this study were electricigens which are in conformity to previous studies [, , 30, 58, 61]. Electricigens are essential as biocatalysts for MFCs. In MFCs, several isolated electricigens are employed. However, most of these electricigens belong to Proteobacteria and Firmicutes. Diverse types of electricigens have various electron transmission methods and capacities, which directly impact on the performance of MFC and are critical in determining the performance and application of the MFC [60]. The majority class of electricigens, which are the dominating strains in the microbial communities of MFCs, are represented by Proteobacteria. Many are capable of transferring electrons directly to the electrode. In the Proteobacteria phylum, electricigens are widely distributed in α-proteobacteria, β-proteobacteria, δ-proteobacteria and γ-proteobacteria [10]. Short-chain fatty acids and aromatic acids, such as cyclohexane-1-carboxylate, benzoate, or butyrate, are broken down by the metabolic expert proteobacteria into acetate, CO2, formate, and H2. However, to remove H2 and formate and maintain thermodynamically favourable catabolic processes, the system needs a hydrogenotrophic partner [6]. Proteobacteria typically carry out the direct electron transfer to the electrode [57], while Bacteroidetes are associated with the hydrolysis of complex macromolecular carbohydrates [, 13, 54]. There are reports that Phylum Actinobacteria ferment pentoses and metabolize oligosaccharides to yield lactic and acetic acids. These bacteria develop best at optimum temperature and pH ranges of 39–41 °C and 6.4–7.0 respectively. They were first discovered as symbionts in the human intestine [, 9, 59]. These pH and temperature (mesophilic) values are in agreement with this study. Generally, Bacteriodetes, Firmicutes and Proteobacteria are the predominant phyla and comprise mainly of acidogenic bacteria. The hydrolysate monomers are fermented by these bacteria into acetate, alcohol, butyrate, propionate, CO2, H2, and other solvents. They have significant impacts on VFA concentration and distribution, which are also influenced by other AD digester's working parameters [6]. Firmicutes and Proteobacteria, which are the first and fifth most dominant phyla respectively in this study, are sulfate-reducing bacteria (SRBs). To oxidize organic materials and produce H2S, they use sulfate as an electron acceptor [29]. They break down propionate and butyrate which act as carbon sources and electron donors/acceptors to produce acetate, either independently or in syntrophic conjunction with hydrogen-scavenging methanogens [6]. The great efficiency of methane production and organic carbon removal in the biodigesters can be linked to the presence of Proteobacteria, Bacteroidetes, Firmicutes, and Actinobacteria. However, the results revealed that the electrochemically active bacteria including Proteobacteria, Actinobacteria, Firmicutes, and Acidobacteria are present in higher proportions. Similarly, some previous works have reported the existence of exoelectrogenic bacterial species [, , , 30, 40, 58, 61].

At the class level, Bacilli, Bacteroidia, Actinobacteria, Clostridia, Unclassified at Class level, Erysipelotrichia, Negativicutes and Chloroplast were the most abundant bacterial communities. Furthermore, evaluating the bacterial taxonomy, a total of 206 types of OTUs (operational taxonomic units) were identified thus, revealing the diversities of bacterial microorganisms in the bioreactors. The most abundant genus is the Lactobacillus (Fig. 9), followed by the genus Bacteroides, as was reported by Giwa et al. [21]. These are typically present in anaerobic environments, where they primarily act as fermenters and acidogens. Hydrogenotrophic methanogen (Fig. 10) dominated the archaeal community density. Methanobrevibacter was the most detected methanogen at the genus level with a relative abundance of 75%, out-striving the Methanomassiliicoccus. Methanobrevibacter and Methanomassiliicoccus which exhibited a synergistic effect on methanogenic pathways. This conjointly enhanced the productivity of methane. Firmicutes, as well as Proteobacteria, have shown to have a dual purpose in the context of this study, as they aid both biogas production (hydrolytic, acidogenic and acetoclastic stages of biogas production) and bioelectricity generation as electricigen. This is in agreement with the work of Quashie et al. [46].

Fig. 9
figure 9

Bacterial dynamic in the amended digestate after 15-day HRT

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Fig. 10
figure 10

Percentage frequency methanogens community dynamics of CPL digestate

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Additional studies would be essential in providing unambiguous experimental proof for the positive impact of higher biochar dosage and its effect on microbial dynamics. Furthermore, different kinds of biochar from different feedstock subjected to varying environmental conditions should be investigated in subsequent MFCs operations via an integrated biorefinery approach.

Conclusion

This study demonstrated an innovative bio-refinery process that has the potential for utilizing pyrolyzed cassava stem biochar mixed cassava waste peels (CPL) amended with cow dung in anaerobic digestion (AD) to simultaneously improve wastewater treatment, generate electricity and produce biogas and biofertilizer for agricultural benefits in MFCs. This concept has the potential for wastewater treatment through COD reduction which was observed to be highest (approximately 81%) with the addition of 10 g biochar in CPL slurries. The optimum power density elicited by CPL waste seeded with 30 g biochar (94.33 ± 2.99 mW/m2) was about 7.36-fold higher than the value (12.81 ± 2.1 mW/m2) produced with the control (CPL waste without biochar). The cumulative volume of biogas produced after the 15-day HRT was 79 ± 0.14 ml. Analysis of the microbial community of the slurry digestate showed that Methanomassiliicoccus and Methanobrevibacter were the main dominant methanogens present as methane formers while the bacterial phyla Firmicutes, Bacteroidetes, Actinobacteria and Proteobacteria were dominant as electricigens for electricity generation. Some physicochemical parameters of the CPL slurry digestate, such as organic carbon, volatile solids, and COD, were significantly reduced after anaerobic digestion. When the anaerobic digestate was seeded with locally isolated potassium and phosphate solubilizers (biofertilizers) and applied on the loam soil, the total length of the planted Zea mays increased by about 68.8% when compared to the control (without biofertilizer). The preferred optimal dosage range for a 4-L working volume in 5L digester batch AD operation was found to be 20–30 g biochar and not 10 g biochar. This study offers increased knowledge on cassava processing wastes beneficiation/value addition, and further explains the mechanism of biochar action in MFCs. The advocacy of large-scale production and application of this biorefinery approach will ultimately reduce our dependency on fossil fuels and chemical fertilizers which are deleterious to the environment and human.