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Aims The purpose of this study was to apply cDNA approach for the characterization of active prokaryotic community to understand microbial scenarios and performance of an AnSBR digester fed with acid hydrolysates of Agave tequilana var. azul bagasse (ATAB). Methods and results The digester was implemented for methane production under organic loading rate (OLR) disturbances to correlate physicochemical variables with changes in abundance, diversity and population dynamics of active Bacteria and Archaea by principal components analysis (PCA). Results indicated that methane yield increased as well as active syntrophic relationships for interspecies hydrogen/formate (Anaerolinaceae-Methanobacterium beijingense) and acetate (Anaerolinaceae-Methanosaeta concilii) transfers at 8 g-COD l-1 day-1 . However, methane yield was negatively affected at 16 g-COD l-1 day-1 due to the competition for acetate by active Desulfovibrio marrakechensis and volatile fatty acids inhibition. Conclusions Microbial scenarios obtained by PCA correlations indicated that methane production from acid hydrolysates of ATAB was feasible at 8 g-COD l-1 day-1 . The digester operation at higher OLR only favoured methanogenesis by the hydrogenotrophic pathway. Significance and impact of the study Only cDNA analysis showed Archaea population dynamics, exhibiting high correlation with physicochemical variables towards the understanding of the methanogenic digester performance during OLR disturbances.

Sequential 2k factorial and central composite designs were used to optimize Agave tequilana bagasse (ATB) pretreatment by using 1-ethyl-3-methylimidazolium acetate ([Emim][OAc]). Reaction time, temperature and solids loading were the studied factors while sugar yield was the response variable. Results indicated that optimal conditions (119 °C, 142 min) using high solids loading (30%) were achieved at lower temperatures and reaction times than those previously reported in the literature. It was also revealed that solid recovery after pretreatment with [Emim][OAc] is a key factor. The increase in enzymatic digestibility of pretreated ATB was correlated to a decrease in crystallinity and lower lignin content as observed using microscopy techniques and weaken chemical bonds by Fourier transform infrared spectroscopy. Yields of glucose and xylose in the hydrolysate were 41.3, and 13.0 kg per 100 kg of untreated ATB, which are equivalent to glucan and xylan conversions of 75.9% and 82.9%, respectively.

The aim of this work was to compare the biohydrogen production potential of undetoxified and detoxified acid hydrolysates from A. tequilana bagasse. Detoxification was carried out with activated carbon at different concentrations and pH values. Results indicated that pH was not a significant variable, while the lowest evaluated concentration of activated carbon (1% p/v) significantly promoted the highest removal of acetic acid (89%) with minimal losses of fermentable sugars. Regarding dark fermentation experiments, central composite designs were used to optimize COD and pH variables for both substrates, undetoxified and detoxified hydrolysates (activated carbon 1% p/v and pH 0.6). At optimal conditions, the detoxified hydrolysate produced 33% more biohydrogen than the undetoxified one. Hydrogen molar yields were 1.71 and 1.23 mol H2/molsugar, respectively. This improvement was correlated to changes in metabolic byproducts, since the detoxified hydrolysate produced only acetic and butyric acids, while lactic acid was detected in the undetoxified hydrolysate.

Agave tequilana bagasse is the main solid waste of the tequila manufacturing and represents an environmental issue as well as a potential feedstock for biofuel production due to its lignocellulosic composition and abundance. In this contribution, this feedstock was subjected to pretreatments with HCl and H 2 SO 4 for sugar recovery and methane was produced from the hydrolysates in batch and sequencing batch reactors (AnSBR). Sugar recovery was optimized by using central composite designs at different levels of temperature, acid concentration and hydrolysis time. Results showed that at optimal conditions, the HCl pretreatment induced higher sugar recoveries than the H 2 SO 4 one, 0.39 vs. 0.26 g total sugars/g bagasse. Furthermore, the H 2 SO 4 hydrolysate contained higher concentrations of potential inhibitory compounds (furans and acetic acid). Subsequent anaerobic batch assays demonstrated that the HCl hydrolysate is a more suitable substrate for methane production; a four-fold increase was found. A second optimization by using HCl as acid catalyst and methane production as the response variable demonstrated that softer hydrolysis conditions are required to optimize methane production as compared to sugar recovery (1.8% HCl, 119 °C and 103min vs. 1.9% HCl, 130 °C and 133min). This softer conditions were used to feed an AnSBR for 110 days and evaluate its stability at three different cycle times (5, 3 and 2 days). Results showed stable reactor performances at cycle times of 5 and 3 days, obtaining the highest methane yield and production at 3 days, 0.28 NL CH 4 /g-COD and 1.04 NL CH 4 /d respectively. Operation at shorter cycle times is not advised due to microbial imbalance.

This study examines the performance of an anaerobic fixed-film bioreactor under seasonal operating conditions prevailing in medium and small size Tequila factories: start-up, normal operation and particularly, during the restart-up after a long stop and starvation period. The proposed start-up procedure attained a stable biofilm in a rather short period (28 days) despite unbalanced COD/N/P ratio and the use of non-acclimated inoculum. The bioreactor was restarted-up after being shut down for 6 months during which the inoculum starved. Even when biofilm detachment and bioreactor clogging were detected at the very beginning of restart-up, results show that the bioreactor performed better as higher COD removal and methane yield were attained. CE-SSCP and Q-PCR analyses, conducted on the biofilm prokaryotic communities for each operating condition, confirmed that the high COD removal results after the bioreactor clogging and the severe starvation period were mainly due to the stable archaeal and resilient bacterial populations.

An artificial neural network (ANN) was implemented to model the light profile pattern inside a photobioreactor (PBR) that uses a toroidal light arrangement. The PBR uses Tequila vinasses as culture medium and purple non-sulfur bacteria Rhodopseudomonas palustris as biocatalyzer. The performance of the ANN was tested for a number of conditions and compared to those obtained by using deterministic models. Both ANN and deterministic models were validated experimentally. In all cases, at low biomass concentration, model predictions yielded determination coefficients greater than 0.9. Nevertheless, ANN yielded the more accurate predictions of the light pattern, at both low and high biomass concentration, when the bioreactor radius, the depth, the rotational speed of the stirrer and the biomass concentration were incorporated in the ANN structure. In comparison, most of the deterministic models failed to correlate the empirical data at high biomass concentration. These results show the usefulness of ANNs in the modeling of the light profile pattern in photobioreactors.

The saturated Output-Feedback (OF) control problem for a class of four-state anaerobic digestors with volatile fatty acids (VFAs) measurement is addressed. The reactor must operate about an optimal steady-state, with maximum VFA consumption, that is locally stable but not structurally unstable. The problem is addressed as an interlaced control-observer design within a geometric control framework in the light of passivity, observability, and bifurcation properties. The result is a saturated linear PI OF controller with global robust stability conditions in terms of control gains and limits. The proposed approach is illustrated with a representative case example through numerical simulations.

Anaerobic digestion is a highly nonlinear time-varying process used for biological wastewater treatment which is subject to large disturbances of both influent concentrations and flow rates. These perturbations can lead to the crash of the digester and thus, the dynamics of the main state variables - including biomass - must be closely monitored to use this information in the design and implementation of advanced control schemes. However, such processes still suffer From a lack of reliable and cheap sensors. As a consequence, efficient monitoring, control and decision support systems are needed in order to insure the correct process operation. Particularly, there is an increasing interest on the proposal of Fault Detection and Isolation (FDI) and Fault Detection and Analysis (FDA) integrated systems. In this paper, we propose the use of interval observers in order to detect and isolate sensor faults as well as input changes in biological systems that are not observable. This approach is experimentally implemented on a 1 m 3 pilot scale anaerobic digestion continuous process.

This paper deals with the simultaneous regulation of volatile fatty acids (VFA's) and total alkalinity (TA) in anaerobic digesters. The control scheme is conformed by an output feedback control and an extended Luenberger observer used to estimate the uncertainties associated to the controlled states ( i.e. , kinetics terms and inlet composition). The inlet flow rate is used to regulate the VFA's concentration, whereas an alkali solution is added directly to the digester for the regulation of the TA concentration. The control scheme is evaluated via numerical simulations under different operating conditions. Results show that the control law is capable to regulate the VFA's and TA despite of load disturbances, uncertainties in the kinetics terms, noisy measurements and control inputs restrictions.

A hybrid (continuous–discrete) cascade control is proposed to regulate both, volatile fatty acids (VFA) and chemical oxygen demand (COD) concentrations in two-stage (acidogenic-methanogenic) anaerobic digestion (TSAD) processes. The outer loop is a discrete controller that regulates the COD concentration of the methanogenic bioreactor by using a daily off-line measurement and that modifies the set-point tracked by inner loop, which manipulates the dilution rate to regulate the VFA concentration of the acidogenic bioreactor, estimated by continuous on-line conductivity measurements, avoiding acidification. The experimental validation was conducted in a TSAD process for the treatment of tequila vinasses during 110 days. Results showed that the proposed cascade control scheme was able to achieve the VFA and COD regulation by using conventional measurements under different set-point values in spite of adverse common scenarios in full-scale anaerobic digestion processes. Microbial composition analysis showed that the controller also favors the abundance and diversity toward methane production.

This paper presents the design and the experimental validation of a nonlinear control approach for the regulation of volatile fatty acids (VFA) in an anaerobic digester. Such an approach is conformed by an output feedback control and an extended Luenberger observer which allows the estimation of the uncertain terms associated to the VFA dynamics (i.e., in∞uent composition and kinetic terms). The nonlinear approach is experimentally validated in a 0.528m 3 up-∞ow flxed-bed anaerobic digester used for the treatment of industrial wine distillery wastewater. The experimental results show that the VFA regulation is achieved in spite of uncertain kinetics, restrictions in the control input and unknown load disturbances. Copyright c ∞2007 IFAC

This paper presents an approach to tune the gains of adjustable asymptotic observers on a class of continuous bioreactors. This approach is based on a careful analysis of the error estimation dynamics. The gains calculated with this approach improve the observer performance and guarantee a high convergence rate in the estimation of unmeasured variables with an accurate degree that can be chosen beforehand by the user. This approach was tested through numerical simulations in an anaerobic digestion process for wastewater treatment for the estimation of biomass concentrations, in which the gains obtained actually allowed the adjustable asymptotic observer to estimate the biomass concentrations with absolute precision. In order to show the usefulness of the adjustable asymptotic observer improved with this approach, its performance is compared in the face of the classical asymptotic observer with excellent results.

In this paper an artificial neural network is developed to model a new depollution process that uses sequential cultures of anaerobic bacteria and yeasts to efficiently remove both carbon and nitrogen from wastewaters. A set of batch experimental runs are used to train and test various neural network topologies. It is shown that the neural network accurately tracks the dynamics of the biological species of the yeast reactor in the process and account for the influence of butyric acid, ammonia and pH on the overall efficiency of purification.

A sampled delayed scheme is proposed to regulate the organic pollution level in anaerobic digestion processes by using off-line COD measurements. The proposed scheme is obtained by combining an error feedback control with a steady state estimator to track constant references and attenuate process load disturbances. The controller performance is tested experimentally for the treatment of tequila vinasses over a period of 68 days under different set-point values and several uncertain scenarios which include badly known kinetic parameters and load disturbances. Experimental results show that the COD concentration can be effectively regulated under the influence of set-point changes and high load disturbances by using only a daily off-line COD measurement, which makes the industrial application of the proposed control scheme feasible.

Adresse auteur: Email: rcoronagonzalez@yahoo.com; International audience; Glucose fermentation with Actinobacillus succinogenes was carried out at different initial concentrations of succinic acid (SA(0)) to determine its effect on growth and on the production of succinic acid itself. The specific rates of biomass production, succinic, formic and acetic acids decreased with SA(0) (0-40 g/l). The partially dissociated form of succinic acid had a higher effect on cell growth and production of succinic acid as compared to the non-dissociated forms of the acids, a fact that has not been reported until now. Cell growth fitted the Jerusalimski model, and the Aiba-Shoda model was suitable for quantification of the inhibition for the production of succinic acid. The growth inhibition constants K (is) and K (ip) and their summatory were consistent with the experimental values obtained, i.e., 22 g/l for the produced acids and 38 g/l for total acids that were the limits at which the biomass formation ceased

International audience; The objective of this work was study the e.ect of three pretreatments (alkalinization, thermical treatment, and sonication) on Tequila’s stillages hydrolysis process in acidogenesis stage, through the following response variables: soluble chemical oxygen demand (CODs), total sugar and volatile fatty acids pro.le and the hydrogen production at the time. The stillages were subject to these pretreatments (according to a 23 factorial design); afterward they were transferred to a batch reactor at 35 _C and inoculated with an anaerobic digestor sludge. Multiple response optimization (MRO) analysis was done to .nd the global optimum for the response variables described above. This optimum is able to maximize simultaneously all these variables. It was found adequate to be useful hydrolyzing the organic matter present in Tequila’s stillages. Mathematical models were .tted to observe the estimated e.ects of pretreatments on each response variable, then the MRO was applied

In this paper, a two-phase anaerobic digestion system is considered to control the outlet concentration of both the Volatile Fatty Acids (VFA's) and the organic matter (other than the VFA's) characterized by its Chemical Oxygen Demand. The two-phase system consists of two fixed bed reactors whose dynamics are described by Partial Differential Equations. The recycle flow rates in each reactor are used as the manipulated variables to reach the control objective. The control laws designed here are decoupled and they are tested by means of simulation runs obtaining satisfactory results in spite of system input disturbances and changes on the set points.

Un observateur multi-variable, robuste et non-lineaire, a vitesse de convergence reglable pour des systemes biologiques. Cet article presente un observateur non-lineaire a vitesse de convergence reglable pour les systemes biologiques, dont les principales variables d'etat sont difficilement mesurables. Cet observateur est fonde sur le principe de l'observateur asymptotique, dont l'interet a deja ete largement demontre dans la litterature, mais il est modifie pour permettre a l'utilisateur d'en regler la vitesse de convergence. Il est en particulier demontre au sein de cet article que l'observateur propose fournit des estimations rapides et satisfaisantes vis-a-vis de perturbations affectant le procede, de defaillances du systeme et d'incertitudes parametriques liees au modele utilise, alors que les bonnes proprietes de stabilite et de robustesse de l'observateur asymptotique classique sont preservees. Cet observateur est par ailleurs teste en simulations numeriques en utilisant un modele mathematique d'un procede biologique utilise pour le traitement des eaux usees par digestion anaerobie. Les resultats sont examines et discutes pour illustrer les benefices d'un tel observateur et son applicabilite a de nombreux procedes biologiques.

Biomass production of fodder sorghum (Sorghum sp.) has been tested in a field trial over two harvesting periods under natural meteorological conditions using ammoxidized kraft lignin (AKL) as a slow-release fertilizer and urea as conventional reference. In the course of the first growth cycle, plants treated with urea gave higher biomass yields because of the better solubility of urea in the initial phase. However, during the second cycle AKL treated plants performed better than urea treated sorghum, indicating that nitrogen from AKL became readily available.

A model-based robust control scheme is applied to a continuous bioreactor operating in an non stationary regime. The proposed control algorithm is a fuzzy robust error feedback controller that allows tracking several profiles of the substract concentration, while maintaining the stability conditions of the process. A numerical case study is simulated to test the robustness properties of the proposed controller in the face of parameter uncertainties and changes on load disturbances.

Abstract Classical observers are constructed on the basis of the nature of the measurement signals, namely, a continuous observer requires continuous output measurements. In this work, a novel observer which estimates continuous states when continuous and discrete measurements are available is presented. By resetting the initial condition of the observer at each sample instant, the convergence of the continuous states is guaranteed. The application to the the estimation of substrate and biomass concentrations in an anaerobic wastewater treatment process in which continuous and discrete measurements usually appear, shows the feasibility of the proposed scheme.