Modeling aerobic carbon source degradation processes using titrimetric data and combined respirometric-titrimetric data: experimental data and model structure

Experimental data are presented that resulted from aerobic batch degradation experiments in activated sludge with simple carbon sources (acetate and dextrose) as substrates. Data collection was done using combined respirometric-titrimetric measurements. The respirometer consists of an open aerated vessel and a closed non-aerated respiration chamber for monitoring the oxygen uptake rate related to substrate degradation. The respirometer is combined with a titrimetric unit that keeps the pH of the activated sludge sample at a constant value by addition of acid and/or base. The experimental data clearly showed that the activated sludge bacteria react with consumption or production of protons during aerobic degradation of the two carbon sources under study. Thus, the cumulative amount of added acid and/or base could serve as a complementary information source on the degradation processes. For acetate, protons were consumed during aerobic degradation, whereas for dextrose protons were produced. For both carbon sources, a linear relationship was found between the amount of carbon source added and the amount of protons consumed (in case of acetate: 0.38 meq/mmol) or produced (in case of dextrose: 1.33 meq/mmol) during substrate degradation. A model taking into account substrate uptake, CO(2) production, and NH(3) uptake for biomass growth is proposed to describe the aerobic degradation of a C(x)H(y)O(z)-type carbon source. Theoretical evaluation of this model for reference parameters showed that the proton effect due to aerobic substrate degradation is a function of the pH of the liquid phase. The proposed model could describe the experimental observations with both carbon sources.     

Modeling aerobic carbon oxidation and storage by integrating respirometric, titrimetric, and off-gas CO2 measurements

A method for detailed investigation of aerobic carbon degradation processes by microorganisms is presented. The method relies on an integrated use of the respirometric, titrimetric, and off-gas CO(2) measurements. The oxygen uptake rate (OUR), hydrogen ion production rate (HPR), and the carbon dioxide transfer rate (CTR) resulting from the biological as well as physicochemical processes, coupled with a metabolic model characterizing both the growth and carbon storage processes, enables the comprehensive study of the carbon degradation processes. The method allows the formation of carbon storage products and the biomass growth rates to be estimated without requiring any off-line biomass or liquid-phase measurements, although the practical identifiability of the system could be improved with additional measurements. Furthermore, the combined yield for biomass growth and carbon storage is identifiable, along with the affinity constant with respect to the carbon substrate. However, the individual yields for growth and carbon storage are not identifiable without further knowledge about the metabolic pathways employed by the microorganisms in the carbon conversion. This is true even when more process variables are measured. The method is applied to the aerobic carbon substrate degradation by a full-scale sludge using acetate as an example carbon source. The sludge was able to quickly take up the substrate and store it as poly-beta-hydroxybutyrate (PHB). The PHB formation rate was a few times faster than the biomass growth rate, which was confirmed by off-line liquid- and solid-phase analysis. The estimated combined yield for biomass growth and carbon storage compared closely to that determined from the theoretical yields reported in literature based on thermodynamics. This suggests that the theoretical yields may be used as default parameters for modeling purposes.     

Development and calibration of bio-kinetic model for surfactant biodegradation with combined respirometric and titrimetric measurements

Substrate removal mechanism in aerobic activated sludge processes was lately modeled using the simultaneous storage and growth (SSAG) phenomenon. The SSAG model was further refined with titrimetric components and successfully calibrated using both respirometric and titrimetric measurements for common substrate acetate. However, the improved SSAG model calibration was not verified with other organic substrates. Furthermore, very few studies are available in the literature on surfactant bio-kinetics, which generally use off-line experimental measurements with limited model-based interpretation. Therefore, the aim of this paper is to demonstrate its applicability for surfactant biodegradation using on-line measurements. Batch experiments were conducted using sodium dodecyl sulfate (SDS) as a test surfactant. Model calibration was done successfully for three different SDS concentrations using respirometric, titrimetric and combined respirometric-titrimetric measurement approaches. The parameter estimation results from all three stated combinations were statistically evaluated and found to be very close validating the model.     

Statistical analysis of nonlinear parameter estimation for Monod biodegradation kinetics using bivariate data

A nonlinear regression technique for estimating the Monod parameters describing biodegradation kinetics is presented and analyzed. Two model data sets were taken from a study of aerobic biodegradation of the polycyclic aromatic hydrocarbons (PAHs), naphthalene and 2-methylnaphthalene, as the growth-limiting substrates, where substrate and biomass concentrations were measured with time. For each PAH, the parameters estimated were: q(max), the maximum substrate utilization rate per unit biomass; K(S), the half-saturation coefficient; and Y, the stoichiometric yield coefficient. Estimating parameters when measurements have been made for two variables with different error structures requires a technique more rigorous than least squares regression. An optimization function is derived from the maximumlikelihood equation assuming an unknown, nondiagonal covariance matrix for the measured variables. Because the derivation is based on an assumption of normally distributed errors in the observations, the error structures of the regression variables were examined. Through residual analysis, the errors in the substrate concentration data were found to be distributed log-normally, demonstrating a need for log transformation of this variable. The covariance between ln C and X was found to be small but significantly nonzero at the 67% confidence level for NPH and at the 94% confidence level for 2MN. The nonlinear parameter estimation yielded unique values for q(max), K(S), and Y for naphthalene. Thus, despite the low concentrations of this sparingly soluble compound, the data contained sufficient information for parameter estimation. For 2-methylnaphthalene, the values of q(max) and K(S) could not be estimated uniquely; however, q(max)/K(S) was estimated. To assess the value of including the relatively imprecise biomass concentration data, the results from the bivariate method were compared with a univariate method using only the substrate concentration data. The results demonstrated that the bivariate data yielded a better confidence in the estimates and provided additional information about the model fit and model adequacy. The combination of the value of the bivariate data set and their nonzero covariance justifies the need for maximum likelihood estimation over the simpler nonlinear least squares regression.     

On‐line adaptive metabolic flux analysis: Application to PHB production by mixed microbial cultures

In this work, an algorithm for on‐line adaptive metabolic flux analysis (MFA) is proposed and applied to polyhydroxybutyrate (PHB) production by mixed microbial cultures (MMC). In this process, population dynamics constitutes an important source of perturbation to MFA calculations because some stoichiometric and energetic parameters of the underlying metabolic network are continuously changing over time. The proposed algorithm is based on the application of the observer‐based estimator (OBE) to the central MFA equation, whereby the role of the OBE is to force the accumulation of intracellular metabolites to converge to zero by adjusting the values of unknown network parameters. The algorithm was implemented in a reactor equipped with on‐line analyses of dissolved oxygen and carbon dioxide through respirometric and titrimetric measurements. The oxygen and carbon dioxide fluxes were measured directly, whereas acetate, PHB, and sludge production fluxes were estimated indirectly using a projection of latent structures model calibrated a priori with off‐line measurements. The algorithm was implemented in a way that the network parameters associated with biosynthesis were adjusted on‐line. The algorithm proofed to converge exponentially with the steady state error always below 1 mmol/L. The estimated fluxes passed the consistency index test for experimental error variances as low as 1%. The comparison of measured and estimated respiratory coefficient and of the theoretical and estimated yield of sludge on acetate further confirmed the metabolic consistency of the parameters that were estimated on‐line. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009     

Biodegradation of chlorferon and diethylthiophosphate by consortia enriched from waste cattle dip solution

Chlorferon and diethylthiophosphate (DETP) are the hydrolysis products of coumaphos, an organophosphate pesticide. In this research, two consortia of bacterial cultures, one responsible for degrading chlorferon and the other for degrading DETP, were selectively enriched from waste cattle dip solution. The enriched cultures were used as inocula to grow biomass for biodegradation studies. For chlorferon degradation, the optimum biomass concentration was found to be 80g/L, and pH 7.5 was selected as the optimal operating pH. Chlorferon degradation was characterized by substrate inhibition kinetics with parameter values estimated to be V(m)=0.062+/-0.011mg/(g-biomass)h, K(m)=21+/-7mg/L, and K(Si)=118+/-45mg/L. For DETP degradation, the optimum biomass concentration was found to be 60g/L, and the optimum pH was in the range of 7.5-8. DETP degradation was characterized by Michaelis-Menten kinetics with parameter values estimated to be V(m)=1.52+/-0.10mg/(g-biomass)h and K(m)=610+/-106mg/L.     

Issues in the culture of the extremely thermophilic methanogen, Methanothermus fervidus

Basic issues in the culture of the extremely thermophilic archaeon, Methanothermus fervidus, have been investigated, including culture medium formulation, substrate yield and product yield coefficient, growth rate and stoichiometry, and H(2) uptake kinetics. The pH optimum for growth of this organism was estimated at 6.9. Growth medium buffered with PIPES instead of bicarbonate supported both increased growth rate and maximum biomass concentration. Substitution of titanium(III) citrate for the reducing agent sodium sulfide improved culture performance as well. However, independent adjustment of iron and nickel concentrations from 11 to 111 muM, respectively, and carbon dioxide partial pressure from 5 to 20 psia did not impact the culture of M. fervidus significantly. An elemental balance approach was utilized to aid in design of a defined medium to support growth to a target maximum biomass concentration of at least 1.0 g dry wt/L. The growth of this organism was limited by H(2) availability in this reformulated culture medium. The maximum growth rate and biomass concentration achieved in anaerobic vials with the defined medium was 0.16 h(-1) and 0.74 g dry wt/L, respectively. This maximum biomass concentration was a 72% improvement over that obtained with a literature-based defined medium. The Monod parameter, K(s), with H(2) as limiting substrate, was estimated at 1.1 +/- 0.4 psia (55 +/- 20 muM in the broth), based on a H(2) consumption study. Representative values for the substrate yield, Y(X/CO(2) ), and product yield coefficient, Y(CH(4)/) (X), were determined experimentally to be 1.78 +/- 0.04 g dry wt/mol CO(2), and 0.52 +/- 0.01 mol CH(4)/g dry wt, respectively. A bench-scale fermentation system suitable for the culture of extremely thermophilic anaerobes was designed and constructed and proved effective for the culture of M. fervidus. (c) 1993 Wiley & Sons, Inc.     

Interdependence between the aerobic degradation of BPA and readily biodegradable substrates by activated sludge in semi-continuous reactors

The objective of the present work was to analyze the interrelationship between the aerobic degradation of BPA and readily biodegradable substrates by activated sludge (AS) in semi-continuous reactors (SCRs). AS were obtained from three SCRs fed with glucose, acetate or peptone. AS from these reactors were used as inocula for three SCRs that were fed with each biogenic substrate, and for three SCRs that were fed with the biogenic substrate and BPA. In all cases, dissolved organic carbon (DOC), BPA, total suspended solids (TSS) and respirometric measurements were performed. Although BPA could be removed in the presence of all the tested substrates, AS grown on acetate exhibited the longest acclimation to BPA. Reactors fed with peptone attained the lowest TSS concentration; however, these AS had the highest specific BPA degradation rate. Specific DOC removal rates and respirometric measurements demonstrated that the presence of BPA had a negligible effect on the removal of the tested substrates. A mathematical model was developed to represent the evolution of TSS and DOC in the SCRs as a function of the operation cycle. Results suggest that the main effect of BPA on AS was to increase the generation of microbial soluble products. This work helps to understand the relationship between the biodegradation of BPA and readily biodegradable substrates.     

Carbon conversion efficiency and limits of productive bacterial degradation of methyl tert-butyl ether and related compounds

The utilization of the fuel oxygenate methyl tert-butyl ether (MTBE) and related compounds by microorganisms was investigated in a mainly theoretical study based on the Y(ATP) concept. Experiments were conducted to derive realistic maintenance coefficients and K(s) values needed to calculate substrate fluxes available for biomass production. Aerobic substrate conversion and biomass synthesis were calculated for different putative pathways. The results suggest that MTBE is an effective heterotrophic substrate that can sustain growth yields of up to 0.87 g g(-1), which contradicts previous calculation results (N. Fortin et al., Environ. Microbiol. 3:407-416, 2001). Sufficient energy equivalents were generated in several of the potential assimilatory routes to incorporate carbon into biomass without the necessity to dissimilate additional substrate, efficient energy transduction provided. However, when a growth-related kinetic model was included, the limits of productive degradation became obvious. Depending on the maintenance coefficient m(s) and its associated biomass decay term b, growth-associated carbon conversion became strongly dependent on substrate fluxes. Due to slow degradation kinetics, the calculations predicted relatively high threshold concentrations, S(min), below which growth would not further be supported. S(min) strongly depended on the maximum growth rate mu(ma)(x), and b and was directly correlated with the half maximum rate-associated substrate concentration K(s), meaning that any effect impacting this parameter would also change S(min). The primary metabolic step, catalyzing the cleavage of the ether bond in MTBE, is likely to control the substrate flux in various strains. In addition, deficits in oxygen as an external factor and in reduction equivalents as a cellular variable in this reaction should further increase K(s) and S(min) for MTBE.     

On-line monitoring of PHB production by mixed microbial cultures using respirometry,titrimetry and chemometric modelling

This work describes a method for on-line monitoring of biomass production, acetate consumption and intracellular polyhydroxybutyrate (PHB) storage by mixed microbial cultures (MMC). The method is based on reliable and easily available on-line measurements, namely pH, dissolved oxygen, dissolved carbon dioxide, on-line respirometry and on-line titrimetric analysis. Biomass production refers to active biomass growth and also to the synthesis of extracellular polymeric substances (EPS). The composition and kinetics of EPS synthesis has high variability depending on the culture enrichment protocol. Since the metabolism for EPS production is rather difficult to define, it was not possible to develop a reliable estimation model based on metabolic principles only. Instead, projection of latent structures (PLS) linear regression constrained by steady state carbon balance was employed. PHB concentration and biomass production rate were directly estimated by the PLS model, whereas acetate concentration was indirectly estimated through the carbon balance. The method was validated experimentally with data of four experiments carried out in a SBR. Accurate on-line estimations were obtained with regression coefficients (r²) of 0.986 and 0.980 for biomass concentration, 0.976 and 0.999 for PHB and 0.992 and 0.999 for acetate concentration in calibration and validation, respectively. These results confirm the ability of the proposed methodology for on-line monitoring of the state variables in PHB production process by MMC.     

A critical comparison of extant batch respirometric and substrate depletion assays for estimation of nitrification biokinetics

Estimation of nitrification biokinetics has been conducted using different batch techniques via measurement of nitrogen species or surrogates such as oxygen (respirometry). However, there are no reports that specifically compare kinetic parameters estimated from respirometry with those from direct nitrogen species measurements. In this study, we evaluated the ability of parameter estimates from isolated and optimally designed complete extant respirometric assays to describe concurrently obtained ammonia and nitrite depletion profiles. Additionally, we mapped the different parameter sets to steady-state bioreactor performance. Using multivariate analysis of variance, we found that estimates from respirometric and substrate depletion assays were predominantly statistically different at the 95% confidence level. The sensitivity of predicted stead-state nitrifying reactor performance to differences in parameter estimates was highest close to the limiting solids retention time (SRT). However, at characteristic nitrifying SRTs the predicted reactor performance using parameter estimates from respirometry and substrate depletion assays were in very close correspondence. Therefore, parameters estimated from extant respirometric assays can be used to adequately predict nitrifying reactor performance.     

Simplified modeling of fed-batch alcoholic fermentation of sugarcane blackstrap molasses

Simplified modeling based on material balances for biomass, ethanol and substrate was used to describe the kinetics of fed-batch alcohol fermentation of sugarcane blackstrap molasses. Maintenance requirements were previously shown to be of particular significance in this system, owing to the use of massive inoculum to minimize inhibitions; therefore, they were taken into consideration for kinetic modeling. Average values of biomass and ethanol yields, productivities, and substrate consumption rates, calculated at the end of runs performed either at constant or exponentially varying flow rates, demonstrated that all of these parameters were influenced by the initial sugar-feeding rate, F(o)S(o). Under conditions of substrate shortage (F(o)S(o) 相似文献   

Uncertainty analysis of forest carbon sink forecast with varying measurement errors: a data assimilation approach

Aims Accurate forecast of ecosystem states is critical for improving natural resource management and climate change mitigation. Assimilating observed data into models is an effective way to reduce uncertainties in ecological forecasting. However, influences of measurement errors on parameter estimation and forecasted state changes have not been carefully examined. This study analyzed the parameter identifiability of a process-based ecosystem carbon cycle model, the sensitivity of parameter estimates and model forecasts to the magnitudes of measurement errors and the information contributions of the assimilated data to model forecasts with a data assimilation approach.Methods We applied a Markov Chain Monte Carlo method to assimilate eight biometric data sets into the Terrestrial ECOsystem model. The data were the observations of foliage biomass, wood biomass, fine root biomass, microbial biomass, litter fall, litter, soil carbon and soil respiration, collected at the Duke Forest free-air CO₂ enrichment facilities from 1996 to 2005. Three levels of measurement errors were assigned to these data sets by halving and doubling their original standard deviations.Important findings Results showed that only less than half of the 30 parameters could be constrained, though the observations were extensive and the model was relatively simple. Higher measurement errors led to higher uncertainties in parameters estimates and forecasted carbon (C) pool sizes. The long-term predictions of the slow turnover pools were affected less by the measurement errors than those of fast turnover pools. Assimilated data contributed less information for the pools with long residence times in long-term forecasts. These results indicate the residence times of C pools played a key role in regulating propagation of errors from measurements to model forecasts in a data assimilation system. Improving the estimation of parameters of slow turnover C pools is the key to better forecast long-term ecosystem C dynamics.     

Fluxes of carbon, phosphorylation, and redox intermediates during growth of saccharomyces cerevisiae on different carbon sources

In the present work we develop a method for estimating anabolic fluxes when yeast are growing on various carbon substrates (glucose, glycerol, lactate, pyruvate, acetate, or ethanol) in minimal medium. Fluxes through the central amphibolic pathways were calculated from the product of the total required amount of a specified carbon intermediate times the growth rate. The required amount of each carbon intermediate was estimated from the experimentally determined macromolecular composition of cells grown in each carbon source and the monomer composition of macromolecules.Substrates sharing most metabolic pathways such as ethanol and acetate, despite changes in the macromolecular composition, namely carbohydrate content (34% +/- 1 and 21% +/- 3, respectively), did not show large variations in the overall fluxes through the main amphibolic pathways. For instance, in order to supply anabolic precursors to sustain growth rates in the range of 0.16/h to 0.205/h, similar large fluxes through Acetyl CoA synthase were required by acetate (4.2 mmol/hr g dw) or ethanol (5.2 mmol/h g dw).The V(max) activities of key enzymes of the main amphibolic pathways measured in permeabilized yeast cells allowed to confirm, qualitatively, the operation of those pathways for all substrates and were consistent on most substrates with the estimated fluxes required to sustain growth.When ATP produced from oxidation of the NADH synthesized along with the key intermediary metabolites was taken into account, higher Y(ATP) (max) values (36 with respect to 24 g dw/mol ATP) were obtained for glucose. The same result was obtained for glycerol, ethanol, and acetate. A yield index (YI) was defined as the ratio of the theoretically estimated substrate flux required to sustain a given growth rate over the experimentally measured flux of substrate consumption. Comparison of Yl between growth on various carbon sources led us to conclude that ethanol (Yl = 0.84), acetate (Yl = 0.77), and lactate (Yl = 0.77) displayed the most efficient use of substrate for biomass production. For the other substrates, the Yl decayed in the following order: pyruvate > glycerol > glucose.An improvement of the quantitative understanding of yeast metabolism, energetics, and physiology is provided by the present analysis. The methodology proposed can be applied to other eukaryotic organisms of known chemical composition. (c) 1995 John Wiley & Sons, Inc.     

Utilization of statistics and experimental design in data collection and analysis

Application of experimental design techniques to Pirt's yield model shows that it is important to collect data at the lowest and highest specific growth rates. In the fed-batch fermentation process, values of specific growth rate can be varied from the maximum value at the start of the process to very low values near the end of the experiment. Candida utilis was cultivated using batch followed by fed-batch culture with glucose as the main source of carbon and energy. Values of substrate concentration, oxygen consumption, carbon dioxide evolution, liquid volume, flow rate cell concentration, and nitrogen concentration, which was an indirect measure of biomass, were measured. Least-squares estimates of the true biomass energetic yield and maintenance coefficient were obtained using a multivariate statistical analysis procedure referred to as the covariate adjustment procedure. Methods of selecting the best estimates using covariate adjustment are illustrated. The results show that useful parameter estimates with relatively short confidence intervals can be obtained using these statistical methods.     

The Low Biomass Yields of the Acetic Acid Bacterium Acetobacter pasteurianus Are Due to a Low Stoichiometry of Respiration-Coupled Proton Translocation

Growth energetics of the acetic acid bacterium Acetobacter pasteurianus were studied with aerobic, ethanol-limited chemostat cultures. In these cultures, production of acetate was negligible. Carbon limitation and energy limitation were also evident from the observation that biomass concentrations in the cultures were proportional to the concentration of ethanol in the reservoir media. Nevertheless, low concentrations of a few organic metabolites (glycolate, citrate, and mannitol) were detected in culture supernatants. From a series of chemostat cultures grown at different dilution rates, the maintenance energy requirements for ethanol and oxygen were estimated at 4.1 mmol of ethanol (middot) g of biomass(sup-1) (middot) h(sup-1) and 11.7 mmol of O(inf2) (middot) g of biomass(sup-1) (middot) h(sup-1), respectively. When biomass yields were corrected for these maintenance requirements, the Y(infmax) values on ethanol and oxygen were 13.1 g of biomass (middot) mol of ethanol(sup-1) and 5.6 g of biomass (middot) mol of O(inf2)(sup-1), respectively. These biomass yields are very low in comparison with those of other microorganisms grown under comparable conditions. To investigate whether the low growth efficiency of A. pasteurianus might be due to a low gain of metabolic energy from respiratory dissimilation, (symbl)H(sup+)/O stoichiometries were estimated during acetate oxidation by cell suspensions. These experiments indicated an (symbl)H(sup+)/O stoichiometry for acetate oxidation of 1.9 (plusmn) 0.1 mol of H(sup+)/mol of O. Theoretical calculations of growth energetics showed that this low (symbl)H(sup+)/O ratio adequately explained the low biomass yield of A. pasteurianus in ethanol-limited cultures.     

Metabolic flux analysis of the mixotrophic metabolisms in the green sulfur bacterium Chlorobaculum tepidum

The photosynthetic green sulfur bacterium Chlorobaculum tepidum assimilates CO(2) and organic carbon sources (acetate or pyruvate) during mixotrophic growth conditions through a unique carbon and energy metabolism. Using a (13)C-labeling approach, this study examined biosynthetic pathways and flux distributions in the central metabolism of C. tepidum. The isotopomer patterns of proteinogenic amino acids revealed an alternate pathway for isoleucine synthesis (via citramalate synthase, CimA, CT0612). A (13)C-assisted flux analysis indicated that carbons in biomass were mostly derived from CO(2) fixation via three key routes: the reductive tricarboxylic acid (RTCA) cycle, the pyruvate synthesis pathway via pyruvate:ferredoxin oxidoreductase, and the CO(2)-anaplerotic pathway via phosphoenolpyruvate carboxylase. During mixotrophic growth with acetate or pyruvate as carbon sources, acetyl-CoA was mainly produced from acetate (via acetyl-CoA synthetase) or citrate (via ATP citrate lyase). Pyruvate:ferredoxin oxidoreductase converted acetyl-CoA and CO(2) to pyruvate, and this growth-rate control reaction is driven by reduced ferredoxin generated during phototrophic growth. Most reactions in the RTCA cycle were reversible. The relative fluxes through the RTCA cycle were 80～100 units for mixotrophic cultures grown on acetate and 200～230 units for cultures grown on pyruvate. Under the same light conditions, the flux results suggested a trade-off between energy-demanding CO(2) fixation and biomass growth rate; C. tepidum fixed more CO(2) and had a higher biomass yield (Y(X/S), mole carbon in biomass/mole substrate) in pyruvate culture (Y(X/S) = 9.2) than in acetate culture (Y(X/S) = 6.4), but the biomass growth rate was slower in pyruvate culture than in acetate culture.     

The structural identifiability of susceptible–infective–recovered type epidemic models with incomplete immunity and birth targeted vaccination

This paper considers the implications of a structural identifiability analysis on a series of fundamental three-compartment epidemic model structures, derived around the general SIR (susceptible–infective–recovered) framework. The models represent various forms of incomplete immunity acquired through natural infection, or from administration of a birth targeted vaccination programme. It is shown that the addition of a vaccination campaign has a negative effect on the structural identifiability of all considered models. In particular, the actual proportion of vaccination coverage achieved, an essential parameter, cannot be uniquely estimated from even ideal prevalence data.     

Modeling product formation in anaerobic mixed culture fermentations

The anaerobic conversion of organic matter to fermentation products is an important biotechnological process. The prediction of the fermentation products is until now a complicated issue for mixed cultures. A modeling approach is presented here as an effort to develop a methodology for modeling fermentative mixed culture systems. To illustrate this methodology, a steady-state metabolic model was developed for prediction of product formation in mixed culture fermentations as a function of the environmental conditions. The model predicts product formation from glucose as a function of the hydrogen partial pressure (P(H2)), reactor pH, and substrate concentration. The model treats the mixed culture as a single virtual microorganism catalyzing the most common fermentative pathways, producing ethanol, acetate, propionate, butyrate, lactate, hydrogen, carbon dioxide, and biomass. The product spectrum is obtained by maximizing the biomass growth yield which is limited by catabolic energy production. The optimization is constrained by mass balances and thermodynamics of the bioreactions involved. Energetic implications of concentration gradients across the cytoplasmic membrane are considered and transport processes are associated with metabolic energy exchange to model the pH effect. Preliminary results confirmed qualitatively the anticipated behavior of the system at variable pH and P(H2) values. A shift from acetate to butyrate as main product when either P(H2) increases and/or pH decreases is predicted as well as ethanol formation at lower pH values. Future work aims at extension of the model and structural validation with experimental data.     

Analysis and application of ADM1 for anaerobic methane production

An anaerobic model for the serum bottle test was developed and analyzed with sensitivities of stoichiometric and kinetic parameters to the components in order to establish a basis for appropriate application of the model. Anaerobic glucose degradation in a serum bottle was selected as an example. The anaerobic model was developed based on the anaerobic digestion model no. 1 (ADM1), which had five processes with 17 kinetic and stoichiometric parameters. Sensitivity analysis showed that the yield of product on the substrate (f) has high sensitivities to model components, and that the methane concentration was the most sensitive component. Important parameters including yield of product on the substrate (f), yield of biomass on the substrate (Y), and half-saturation values (K) were estimated using genetic algorithms, which optimized the parameters with experimental results. The Monod maximum specific uptake rate (k) was, however, so strongly associated with the concentration of biomass, that values could not be estimated individually. Simulation with estimated parameters showed good agreement with experimental results in the case of methane production. However, there were some differences in acetate and propionate concentrations.