Effect of Substrate to Inoculum Ratio on Biogas Production and Microbial Community During Hemi-Solid-State Batch Anaerobic Co-digestion of Rape Straw and Dairy Manure

Impact of using glucose as a sole carbon source to analyze the effect of biochar on the kinetics of biomethane production

The adaptation of biochar in anaerobic digestion (AD) positively influences the conversion of substrate to biomethane and promotes system stability. This study investigated the influence of biochar (BC) doses (0 to 8 g/L) on the Biochemical Methane Potential (BMP) of glucose during a 60-day AD in a mesophilic batch-type reactor. The first 6.5 weeks of the experimentation were dedicated to the microorganism's adaptation to the biochar and degradation of organics from the used inoculum (3 phases of the glucose feeding). The last 2 weeks (4th phase of glucose feeding) represented the assumption, that glucose is the sole carbon source in the system. A machine learning model based on the autoregressive integrated moving average (ARIMA) method was used to model the cumulative BMP. The results showed that the BMP increased with the amount of BC added. The highest BMP was obtained at a dose of 8 g/L, with a maximum cumulative BMP of 390.33 mL CH4/g-VS added. Likewise, the system showed stability in the pH (7.17 to 8.17). In contrast, non-amended reactors produced only 135.06 mL CH4/g-VS and became acidic at the end of the operation. Reducing the influence of carbon from inoculum, sharpened the positive effect of BC on the kinetics of biomethane production from glucose.

Influence of Pre-Incubation of Inoculum with Biochar on Anaerobic Digestion Performance

The application of biochar as an additive to enhance the anaerobic digestion (AD) of biomass has been extensively studied from various perspectives. This study reported, for the first time, the influence of biochar incubation in the inoculum on the anaerobic fermentation of glucose in a batch-type reactor over 20 days. Three groups of inoculum with the same characteristics were pre-mixed once with biochar for different durations: 21 days (D21), 10 days (D10), and 0 days (D0). The BC was mixed in the inoculum at a concentration of 8.0 g/L. The proportion of the inoculum and substrate was adjusted to an inoculum-to-substrate ratio of 2.0 based on the volatile solids. The results of the experiment revealed that D21 had the highest cumulative methane yield, of 348.98 mL, compared to 322.66, 290.05, and 25.15 mL obtained from D10, D0, and the control, respectively. Three models-modified Gompertz, first-order, and Autoregressive Integrated Moving Average (ARIMA)-were used to interpret the biomethane production. All models showed promising fitting of the cumulative biomethane production, as indicated by high R2 and low RMSE values. Among these models, the ARIMA model exhibited the closest fit to the actual data. The biomethane production rate, derived from the modified Gompertz Model, increased as the incubation period increased, with D21 yielding the highest rate of 31.13 mL/gVS. This study suggests that the application of biochar in the anaerobic fermentation of glucose, particularly considering the short incubation period, holds significant potential for improving the overall performance of anaerobic digestion.

Prediction of biogas production of industrial scale anaerobic digestion plant by machine learning algorithms

In the anaerobic digestion (AD) process there are some difficulties in maintaining process stability due to the complexity of the system. The variability of the raw material coming to the facility, temperature fluctuations and pH changes as a result of microbial processes cause process instability and require continuous monitoring and control. Increasing continuous monitoring, and internet of things applications within the scope of Industry 4.0 in AD facilities can provide process stability control and early intervention. In this study, five different machine learning (ML) algorithms (RF, ANN, KNN, SVR, and XGBoost) were used to describe and predict the correlation between operational parameters and biogas production quantities collected from a real-scale anaerobic digestion plant. The KNN algorithm had the lowest accuracy in predicting total biogas production over time, while the RF model had the highest prediction accuracy of all prediction models. The RF method produced the best prediction, with an R² of 0.9242, and it was followed by XGBoost, ANN, SVR, and KNN (with R² values of 0.8960, 0.8703, 0.8655, 0.8326, respectively). Real-time process control will be provided and process stability will be maintained by preventing low-efficiency biogas production with the integration of ML applications into AD facilities.

Investigations into valorisation of trade wastewater for biomethane production

Biogas production from wastewater is one way that industrial sites can work towards the UN Sustainable Development Goals, while recovering a valuable resource. The objective of this study was to investigate the suitability of data collected by municipal wastewater service providers as a method of classifying and screening waste producers as potential sites for biogas resource recovery by anaerobic digestion. Industrial wastewater samples, including raw effluent and treated waste ready for discharge, were examined, and biomethane potential assays performed. Results of chemical analysis and lab-scale digestion were compared to historical service provider data, and patterns were observed. Biomethane yields of up to 357 mL/gVS and 287mL/gVS were achieved from raw and treated effluent respectively. Digestion at the top four prospects could produce over 4690 GJ of methane and save $47,000 in natural gas costs, offsetting 490 tonnes of CO2 equivalent annually. These streams, from logistics, waste management, food and animal product businesses, combined high levels of degradable substrates and low levels of inhibitory components. While it is unlikely that this type of screening program can be completely accurate, certain parameters, including high sodium concentration, are applicable for discounting the potential for biogas production. This knowledge can be a valuable tool in the process of selecting sites for future resource recovery, therefore increasing the uptake of these processes, resulting in economic, environmental, and climate change mitigation benefits.

Long-term inhibition of chlortetracycline antibiotics on anaerobic digestion of swine manure

This study aimed to identify whether chronic effects are present in the anaerobic digestion (AD) of swine manure (SM) containing chlortetracycline (CTC), which is one of the major broad-spectrum veterinary antibiotics, and to elucidate the long-term inhibitory effects and recovery from the inhibition based on AD performance and microbial community. Two continuous-stirred tank reactors treating SM with and without CTC spiking (3 mg/L) were operated for 900 days. Due to the degradation and transformation, the total concentration including CTC's epimer and isomer in the test reactor was 1.5 mg/L. The exposure level was determined according to probabilistically estimated concentrations with uncertainties in field conditions. Until the cessation of CTC exposure on day 585, the methane generation of test reactor continuously decreased to 55 ± 17 mL/g-VS/day, 53% that of control. The methane generation and organic removal were not recovered within 300 days after the CTC exposure was stopped. During the experiment, stability parameters such as pH, total ammonium nitrogen, the composition of methane and alkalinity were the same for both reactors. The concentration and composition of VFAs in the test reactor were different with those of control but not in inhibition level. Microbial profiles revealed that reduction in bacterial diversity and changed balance in microbial species resulted in the performance downgrade under the long-term antibiotic pressure. Since it is hard to recover from the inhibition and difficult to predict the inhibition using physicochemical indicators, continuous exposure to CTC needs to be avoided for the sustainable management of AD plants treating SM.

Semi-solid anaerobic co-digestion of source-separated fecal slag and food waste: focusing on methane production, ecological risk assessment, and quality evaluation as fertilizer

Toilet revolution is driven by the urgent need for solutions to improve sanitation and access to high-quality organic fertilizer for rural areas, which is tagged "resource recovery from human waste." This study provides a possible solution via semi-solid anaerobic co-digestion (Aco-D) of source-separated fecal slag (SFS) and food waste (FW) (3:1). A comprehensive investigation of Aco-D at different inoculum/substrate ratios (ISR) was conducted. Results revealed that the reactor with ISR of 1:4 reached the highest methane yield (255.05 mL/gVS), which enhanced Methanosaetaceae, Methanomicrobiales, and Syntrophomonas. Additionally, the reactor with low feedstock (ISR of 1:2) showed higher removal efficiency of antibiotics (74.75%). The ecological risk of digestate decreased to an insignificant hazard quotient level, and the contents of nutrients and heavy metals were in line with the standard requirement for fertilizer. This study could serve as an alternative technology to support further research in SFS management and digestate utilization as fertilizer.

Deeper insights into the effects of substrate to inoculum ratio selection on the relationship of kinetic parameters, microbial communities, and key metabolic pathways during the anaerobic digestion of food waste

The substrate to inoculum ratio (S/I) is a crucial factor that affects not only the stability of the anaerobic digestion (AD) of food waste (FW) but also the methanogenic capacity of the substrate. This is of great significance for the start-up of small-scale batch reactors and the directional regulation of methanogenesi and organic acid production. Most studies have merely clarified the optimal S/I ratio for methane production and revealed the basic composition of microbial communities. However, the mechanism of microbial interactions and the metabolic pathways behind the optimal S/I ratio still remain unclear. Herein, the effects of different S/I ratios (VS basis) on the relationship of kinetic parameters, microbial communities, and metabolic pathways during the AD process of FW were holistically explored. The results revealed that high S/I ratios (4:1, 3:1, 2:1, and 1:1) were prone to irreversible acidification, while low S/I ratios (1:2, 1:3, and 1:4) were favorable for methanogenesis. Moreover, a kinetic analysis demonstrated that the methane yield of S/I = 1:3 were the highest. A bioinformatics analysis found that the diversity of bacteria and archaea of S/I = 1:3 were the most abundant, and the enrichment of Bacteroides and Synergistetes could help to establish a syntrophic relationship with hydrogenotrophic methanogens, which could aid in the fulfillment of a unique niche in the system. In contrast to the findings with the other S/I ratios, the cooperation among microbes in S/I = 1:3 was more apparent. Notably, the abundances of genes encoding key enzymes involved in the methanogenesis pathway under S/I = 1:3 were all the highest. This knowledge will be helpful for revealing the influence mechanism of the ratio relationship between microorganisms and substrates on the biochemical metabolic process of anaerobic digestion, thereby providing effective guidance for the directional regulation of FW batch anaerobic reactors.

Effects of Stepwise Temperature Shifts in Anaerobic Digestion for Treating Municipal Wastewater Sludge: A Genomic Study

In wastewater treatment plants (WWTP), anaerobic digester (AD) units are commonly operated under mesophilic and thermophilic conditions. In some cases, during the dry season, maintaining a stable temperature in the digester requires additional power to operate a conditioning system. Without proper conditioning systems, methanogens are vulnerable to temperature shifts. This study investigated the effects of temperature shifts on CH₄ gas production and microbial diversity during anaerobic digestion of anaerobic sewage sludge using a metagenomic approach. The research was conducted in lab-scale AD under stepwise upshifted temperature from 42 to 48 °C. The results showed that significant methanogen population reduction during the temperature shift affected the CH₄ production. With 70 days of incubation each, CH₄ production decreased from 4.55 L·g⁻¹-chemical oxygen demand (COD) at 42 °C with methanogen/total population (M·TP⁻¹) ratio of 0.041 to 1.52 L·g⁻¹ COD (M·TP⁻¹ ratio 0.027) and then to 0.94 L·g⁻¹ COD ( M·TP⁻¹ ratio 0.026) after the temperature was shifted to 45 °C and 48 °C, respectively. Methanosaeta was the most prevalent methanogen during the thermal change. This finding suggests that the Methanosaeta genus was a thermotolerant archaea. Anaerobaculum, Fervidobacterium, and Tepidanaerobacter were bacterial genera and grew well in shifted-up temperatures, implying heat-resistant characteristics.

Alleviating nutrient imbalance of low carbon-to-nitrogen ratio food waste in anaerobic digestion by controlling the inoculum-to-substrate ratio

Food waste (FW) characterized by a low carbon/nitrogen (C/N) ratio ranging between 6 and 19 was used to investigate the feasibility and mechanism of maneuvering inoculum-to-substrate ratio (ISR) to alleviate the metabolic imbalance caused by imbalanced nutrients in the AD process, through biochemical methane potential tests and methanogenic pathway analysis. The maximum methane yield of 0.4 L/g of volatile solid (VS) was obtained at a C/N ratio of 11 and an ISR of 10:3. Increasing ISR from 1:2 to 10:3 promoted methane production by ∼20% via an enhancement in acetoclastic methanogenesis and the hydrolysis of carbohydrates and proteins. At lower ISR < 1, hydrogenotrophic methanogenic and syntrophic bacteria dominated, and methane production decreased by ∼ 20% due to the energy disadvantages of syntrophic methanogenesis. Efficient digestion of FW with low C/N ratio FW could be achieved by using metabolic pathways to regulate it and increasing ISR from 1:1 to 10:3.

Substrate-to-inoculum ratio drives solid-state anaerobic digestion of unamended grape marc and cheese whey

Inoculation dose is a key operational parameter for the solid-state anaerobic digestion (SS-AD) of lignocellulosic biomass, maximum methane recovery, and stable digester performance. The novelty of this study was the co-digestion of unamended full-strength grape marc and cheese whey for peak methane extraction at variable inoculation levels. An acclimatised digestate from a preceding anaerobic treatment was used as a downstream inoculum. The impact of inoculum size (wet weight) was evaluated at 0/10, 5/5, 7/3 and 9/1 substrate-to-inoculum (S/I) ratios, corresponding to an initial concentration of 20-30% total solids (TS) in digesters over 58 days at 45°C. The optimal 7/3 S/I produced the highest cumulative methane yield, 6.45 L CH4 kg-1 VS, coinciding with the lowest initial salinity at 11%; the highest volumetric methane productivity rate of 0.289±0.044 L CH4 LWork-1 d-1; the highest average COD/N ratio of 9.88; the highest final pH of 9.13, and a maximum 15.07% elemental carbon removal; for a lag time of 9.4 days. This study identified an optimal inoculation dose and opens up an avenue for the direct co-digestion of grape marc and cheese whey without requirements for substrate pretreatment, thus improving the overall bioenergy profile of the winery and dairy joint resource recovery operations.

Effect of the Substrate to Inoculum Ratios on the Kinetics of Biogas Production during the Mesophilic Anaerobic Digestion of Food Waste

This study evaluates the effects of the varying substrate to inoculum ratios (S:I) of 0.5, 1, 2, 3, 4, 5, and 6 (volatile solids/VS basis) on the kinetics of biogas production during batch mesophilic (35 ± 1 °C) anaerobic digestion (AD) of simulated food waste (FW), using anaerobic digestate as the inoculum. Kinetic parameters during biogas production (scrubbed with NaOH solution) are predicted by the first-order and the modified Gompertz model. The observed average specific biogas yields are in descending order corresponding to the S:I ratios 1, 2, 4, 6, 3, 5, and 0.5, respectively, and the significant effect of the S:I ratio was observed. The tests with the S:I of 1 have the maximum average biogas production rates of 88.56 NmL/gVS.d, whereas tests with the S:I of 6 exhibited the lowest production rates (24.61 NmL/gVS.d). The maximum biogas yields, predicted by the first order and the modified Gompertz model, are 668.65 NmL/gVS (experimental 674.40 ± 29.10 NmL/gVS) and 653.17 NmL/gVS, respectively. The modified Gompertz model has been proven to be suitable in predicting biogas production from FW. VS removal efficiency is greater in higher S:I ratios, with a maximum of 78.80 % at the S:I ratio of 6, supported by the longer incubation time. Moreover, a significant effect of the S:I ratio is seen on kinetics and energy recovery from the AD of FW.

Biomethane Production from Anaerobic Co-Digestion of Selected Organic Fraction of Municipal Solid Waste (OFMSW) with Sewage Sludge: Effect of the Inoculum to Substrate Ratio (ISR) and Mixture Composition on Process Performances

The aim of this study was to evaluate the effect of the inoculum to substrate ratio (ISR) and the mixture ratio between organic fraction of municipal solid waste (OFMSW) and sewage sludge (SS) on the methane production potential achievable from anaerobic co-digestion (AcoD). Biochemical Methane Potential (BMP) assays at mesophilic temperature were used to determine the best AcoD configuration for maximizing methane yield and production rate, as well as to address possible synergistic effects. The maximum methane yield was observed at ISR of 1 and 60% OFMSW: 40% SS as co-digestion mixture, whereas the highest methane production rate was achieved at ISR of 2 with the same mixture ratio (207 mL/gVS/d). Synergistic effects were highlighted in the mixtures having OFMSW below 60%, determining an increase of approximately 40% in methane production than the OFMSW and SS digestion as a sole substrate. The experimental data demonstrated that co-digestion of OFMSW and SS resulted in an increase in the productivity of methane than anaerobic digestion using the sole substrates, producing higher yields or production rates while depending on the ISR and the mixture ratio.

Dynamic Effect of Operational Regulation on the Mesophilic BioMethanation of Grape Marc

Wine production annually generates an estimated 11 million metric tonnes of grape marc (GM) worldwide. The diversion of this organic waste away from landfill and towards its use in the generation of renewable energy has been investigated. This study aimed to evaluate the effectiveness of operational parameters relating to the treatment regime and inoculum source in the extraction of methane from GM under unmixed anaerobic conditions at 35 °C. The study entailed the recirculation of a previously acclimated sludge (120 days) as downstream inoculum, an increased loading volume (1.3 kg) and a low substrate-to-inoculum ratio (10:3 SIR). The results showed that an incorporation of accessible operational controls can effectively enhance cumulative methane yield (0.145 m³ CH₄ kg⁻¹ VS), corresponding to higher amounts of digestible organics converted. The calculated average volumetric methane productivity equalled 0.8802 L CH₄ L_Work⁻¹ d⁻¹ over 33.6 days whilst moderate pollutant removal (43.50% COD removal efficiency) was achieved. Molecular analyses identified Firmicutes and Bacteroidetes phyla as core organisms for hydrolytic and fermentative stages in trophic relationships with terminal electron acceptors from the methane-producing Methanosarcina genus. Economic projections established that the cost-effective operational enhancements were sustainable for valorisation from grape marc by existing wineries and distilleries.

Insights into organic loading rates of anaerobic digestion for biogas production: a review

Anaerobic digestion (AD) for biogas production is affected by many factors that includes organic loading rate (OLR). This OLR appears to be closely linked to various other factors and understanding these linkages would therefore allow the sole use of OLR for process performance monitoring, control, as well as reactor design. This review's objective is to collate the various AD factor specific studies, then relate these factors' role in OLR fluctuations. By further analyzing the influence of OLR on the AD performance, it would then be possible, once all the other factors have been determined and fixed, to manage an AD plant by monitoring and controlling OLR only. Decisions on reactor design, process kinetics, biogas yield and process stability can then be made much more quickly and with minimal troubleshooting steps.

Strategies to improve solid state anaerobic bioconversion of lignocellulosic biomass: an overview

Solid state anaerobic digestion (SSAD) of lignocellulosic biomass may be attractive solution for its valorisation. Compared to liquid state anaerobic digestion (LSAD), SSAD can handle higher organic loading rates (OLR), requires a less water and smaller reactor volume. It may require lower energy demand for heating or mixing and has higher volumetric methane productivity. Besides numerous benefits of SSAD processes and progress in system design, there are still obstacles, which need to be overcome for its successful implementations. This review aims to compile the recent trends in enhancing the bioconversion of agricultural stubbles in SSAD. Several pretreatment procedures used to breaking lignin and cellulose complex, method to overcome carbon to nitrogen ratio imbalance, use of carbon-based conducting materials to enhance Volatile Fatty Acids (VFA) conversion and additives for achieving nutrient balance will be discussed in this review. Leachate recirculation and its impacts on SSAD of agricultural stubbles are also discussed.

Impact of volatile fatty acids to alkalinity ratio and volatile solids on biogas production under thermophilic conditions

The study assessed the impact of volatile fatty acids (VFA) to total alkalinity (TA) ratio (VFA/TA), and percentage volatile solids (VS) reduction of batch and semi-continuous anaerobic co-digestion of palm nut paste waste (PNPW) and anaerobic-digested rumen waste (ADRW) on digester stability and biogas production under the environmental condition of 50 ± 1°C and hydraulic retention time of 21 days for the batch studies and 14 days for semi-continuous co-digestion. The co-digestion ratios were based on percentage digester volume corresponding to 90%:10%, 75%:25% and 50%:50%. During batch and semi-continuous anaerobic co-digestion, VFA/TA of 0.32-1.0 and VS reduction of 53-67% were observed as the stable range at which biogas production was maximum. In terms of semi-continuous anaerobic digestion (AD), except for the 50%:50% ratio where biogas production progressed steadily from the first to fourteenth days, biogas production initially dropped from 180.1 to 171.3 mL between the first and third days of the 90%:10% reaching a maximum of 184 mL on the fourteenth day. Biogas production declined from 198.8 to 187.5 mL on the second day and then increased to 198.8 ± 0.5 mL in the case of the 75%:25% with a significant difference between the treatment ratios at p < 0.05. Therefore, the study can confirm that the 50%:50% ratio (PNPW:ADRW) is a suitable option for managing crude fat-based waste under thermophilic AD due to its potential for rapid start-up and complete biodegradation of active biomass within a 21-day period. This presupposes that residual methane as greenhouse gas will be void in the effluent if disposed of.

Performance prediction of ZVI-based anaerobic digestion reactor using machine learning algorithms

The use of zero-valent iron (ZVI) to enhance anaerobic digestion (AD) systems is widely advocated as it improves methane production and system stability. Accurate modeling of ZVI-based AD reactor is conducive to predicting methane production potential, optimizing operational strategy, and gathering reference information for industrial design in place of time-consuming and laborious tests. In this study, three machine learning (ML) algorithms, namely random forest (RF), extreme gradient boosting (XGBoost), and deep learning (DL), were evaluated for their feasibility of predicting the performance of ZVI-based AD reactors based on the operating parameters collected in 9 published articles. XGBoost demonstrated the highest accuracy in predicting total methane production, with a root mean squared error (RMSE) of 21.09, compared to 26.03 and 27.35 of RF and DL, respectively. The accuracy represented by mean absolute percentage error also showed the same trend, with 14.26%, 15.14% and 17.82% for XGBoost, RF and DL, respectively. Through the feature importance generated by XGBoost, the parameters of total solid of feedstock (TS_f), sCOD, ZVI dosage and particle size were identified as the dominant parameters that affect the methane production, with feature importance weights of 0.339, 0.238, 0.158, and 0.116, respectively. The digestion time was further introduced into the above-established model to predict the cumulative methane production. With the expansion of training dataset, DL outperformed XGBoost and RF to show the lowest RMSEs of 11.83 and 5.82 in the control and ZVI-added reactors, respectively. This study demonstrates the potential of using ML algorithms to model ZVI-based AD reactors.

Biogas Production from Anaerobic Co-Digestion of Spent Mushroom Substrate with Different Livestock Manure

Spent mushroom substrate (SMS) is defined as the biomass waste generated during industrial mushroom cultivation. Utilization of SMS has been extensively researched and has immense potential as a sustainable substrate for generating biogas that can offset fossil fuel use. This closed loop energy generation process that can be set up in mushroom plants will reduce the dependence on fossil fuels and has the potential to reduce greenhouse gas emissions, which will benefit the environment. Anaerobic co-digestion of SMS with different agricultural wastes such as livestock manure would result in enhanced biogas production. In this study, the anaerobic co-digestion of SMS was carried out by combing yellow back fungus SMS along with chicken, dairy and pig manure. SMS combined with chicken manure yielded a slightly higher cumulative methane yield when compared with the combination of dairy manure and pig manure. Factors such as the total solids (TS) and the relative ratio of manure to SMS loading had a significant impact on the cumulative methane yield, volatile solids removal, with a particularly prominent synergistic effect. The synergistic effect was also closely related to the C/N ratio, and under experimental conditions (TS = 15%, SMS relative ratio of 50% and C/N ratio = 25.6), the cumulative methane yield of SMS with chicken manure (CM) was increased by 414% compared with that obtained using SMS or CM separately. We carried out a multiple linear regression (MLR) analysis, a statistical technique that uses several explanatory variables to predict the outcome of a response variable. Our analysis concluded that by using operating conditions (TS = 15%, and SMS ratio = 38.9), we were able to achieve the maximum cumulative methane yield (CMY).

Effects of digestate recirculation ratios on biogas production and methane yield of continuous dry anaerobic digestion

This study conducted a small scale, push flow, continuous, dry anaerobic digestion experiment using 50% and 60% digestate recirculation ratios to investigate the effects of digestate recirculation ratio on continuous dry anaerobic digestion and to analyze microbial community succession. The results showed that the volumetric biogas production rate could reach 1.6 L/L·d during the 60% digestate recirculation ratio. A slight, initial accumulation of volatile fatty acids (VFAs) (maximum concentration 1.6 g/L) was subsequently consumed by the Christensenellaceae R-7 group, and VFA concentrations stabilized at around 20 mg/L. The increased digestate recirculation ratio (60%) promoted both VadinBC27 wastewater-sludge group and Methanobacterium proliferation, and the predominance of those microbial strains may be why VFAs decreased and gas production efficiency improved. Those microbial community changes, fostered by the higher digestate recirculation ratio, are important in continuous dry anaerobic digestion. These results aid continued work aimed at improving continuous, dry anaerobic digestion.

In search of the optimal inoculum to substrate ratio during anaerobic co-digestion of spent coffee grounds and cow manure

The inoculum to substrate (I:S) ratio is a crucial operating parameter during the start-up period of anaerobic digestion (AD) processes and this ratio shows high differentiation with respect to substrate composition. While spent coffee grounds (SCG) have started to gain attraction in AD as a co-substrate due to their vast production and promising methane potential, there is still not enough information on the operative environment of SCG-based biogas reactors. This study investigated the optimal I:S ratio during anaerobic co-digestion of SCG and cow manure. Biochemical methane potential tests were conducted at mesophilic conditions and the influence of I:S ratio on methane production and digestion stability was evaluated at a wide range of I:S ratios from 0.5:1 to 4:1 (volatile solids (VS) basis). Methane yields increased gradually starting from the I:S ratio of 0.5:1 up to 3:1 and the highest methane yield (225 mlCH₄ gVS^-1) was achieved at the I:S ratio of 3:1. Comparatively lower methane yields were obtained at the ratios of 3.5:1 and 4:1. Instable AD conditions were established at the lowest I:S ratio examined (0.5:1), which caused volatile fatty acid (VFA) accumulation. The results highlighted that anaerobic co-digestion of SCG and cow manure is a promising approach, while the I:S ratio should be well-maintained due to the high potential risk of rapid and/or excess VFA production of these feedstocks.