The hydraulic retention time influences the abundance of Enterobacter, Clostridium and Lactobacillus during the hydrogen production from food waste.

The influence of hydraulic retention time (HRT) on the microbial communities was evaluated in an anaerobic sequencing batch reactor (AnSBR) using organic waste from a restaurant as the substrate. The relationship among Lactobacillus, Clostridium and Bacillus as key micro-organisms on hydrogen production from organic solid waste was studied. The effect of the HRT (8-48 h) on the hydrogen production and the microbial community was evaluated. Quantitative PCR was applied to determine the abundance of bacteria (in particular, Enterobacter, Clostridium and Lactobacillus genera). An AnSBR fermentative reactor was operated for 111 cycles, with carbohydrate and organic matter removal efficiencies of 80 ± 15·42% and 22·1 ± 4·49% respectively. The highest percentage of hydrogen in the biogas (23·2 ± 11·1 %), and the specific production rate (0·42 ± 0·16 mmol H2 gVSadded -1 d-1 ) were obtained at an HRT of 48 h. The decrease in the HRT generated an increase in the hydrogen production rate but decreasing the content of the hydrogen in the gas. HRT significantly influence the abundance of Enterobacter, Clostridium and Lactobacillus during the hydrogen production from food waste leading the hydrogen production as well as the metabolic pathways. The microbial analysis revealed a direct relationship between the HRT and the presence of fermentative bacteria (Enterobacter, Clostridium and Lactobacillus genera). Clostridium sp. predominated at an HRT of 48 h, while Enterobacter and Lactobacillus predominated at HRTs between 8 and 24 h. SIGNIFICANCE AND IMPACT OF THE STUDY: Significance and Impact of the Study: It was demonstrated that hydrogen production using food waste was influenced by the hydraulic retention time (HRT), and closely related to changes in microbial communities together with differences in metabolic patterns (e.g. volatile fatty acids, lactate, etc.). The decrease in the HRT led to the dominance of lactic acid bacteria within the microbial community whereas the increase in HRT favoured the emergence of Clostridium bacteria and the increase in acetic and butyric acids. Statistical data analysis revealed a direct relationship existing between the HRT and the microbial community composition in fermentative bacteria. This study provides new insight into the relationship between the bioprocess operation and the microbial community to understand better and control the biohydrogen production.

Electrical conductivity as a state indicator for the start-up period of anaerobic fixed-bed reactors.

The aim of this work was to analyse the applicability of electrical conductivity sensors for on-line monitoring the start-up period of an anaerobic fixed-bed reactor. The evolution of bicarbonate concentration and methane production rate was analysed. Strong linear relationships between electrical conductivity and both bicarbonate concentration and methane production rate were observed. On-line estimations of the studied parameters were carried out in a new start-up period by applying simple linear regression models, which resulted in a good concordance between both observed and predicted values. Electrical conductivity sensors were therefore identified as an interesting method for monitoring the start-up period of anaerobic fixed-bed reactors due to its reliability, robustness, easy operation, low cost, and minimum maintenance compared with the currently used sensors.

Rapid characterization of sulfur and phosphorus in organic waste by near infrared spectroscopy.

Near-infrared spectroscopy (NIRS) has recently emerged as a valuable tool for monitoring organic waste utilized in anaerobic digestion processes. Over the past decade, NIRS has significantly improved the characterization of organic waste by enabling the prediction of several crucial parameters such as biochemical methane potential, carbohydrate, lipid and nitrogen contents, Chemical Oxygen Demand, and kinetic parameters. This study investigates the application of NIRS for predicting the levels of Sulfur (S) and Phosphorus (P) within organic waste materials. The results for sulfur prediction exhibited a high level of accuracy, yielding an error of 1.21 g/Kg[TS] in an independently validated dataset, coupled with an R-squared value of 0.84. Conversely, the prediction of phosphorus proved to be slightly less successful, showing an error of 1.49 g/Kg[TS] with an R-squared value of 0.70. Furthermore, the disparities in performance seem to stem from the inherent correlation between the spectral data and the sulfur or phosphorus contents. Significantly, a variable selection technique known as CovSel was employed, shedding light on the differing approaches used for sulfur and phosphorus predictions. In the case of sulfur, the prediction was achieved through a direct correlation with wavelengths associated with sulfur-related functional groups (such as R - S(=O)2 - OH, -SH, and R-S-S-R) present in the NIR spectra. In contrast, phosphorus prediction relied on an indirect correlation with absorption bands related to organic matter (including CH, CH2, CH3, -CHO, R-OH, C = O, -CO2H, and CONH).

Determination of the optimal feed recipe of anaerobic digesters using a mathematical model and a genetic algorithm.

Recently, numerous experimental studies have been undertaken to understand the interactions between different feedstocks in anaerobic digestion. They have unveiled the potential of blending substrates in the process. Nevertheless, these experiments are time-intensive, prompting the exploration of various optimization approaches. Notably, genetic algorithms have gained interest due to their population-based structures allowing them to efficiently yield multiple Pareto-optimal solutions in a single run. This study uses a simplified static anaerobic co-digestion model as the fitness function for a multi-objective optimization. The optimization aims to achieve a methane production set-point while reducing the output ammonia nitrogen and increasing the recipe' profitability. Thus, the study employs genetic algorithms to identify Pareto fronts and constraints confined the solution space within feasible boundaries. It also underscores the influence of economic considerations on the viable solution space. Ultimately, the optimal feed recipe not only ensures stable operations within the digester but also enhances associated profits.

Consideration of unmeasured micropollutants released from WWTP for potential impact estimations.

During wastewater treatment, micropollutants are only partly eliminated and may present a risk for human health and aquatic ecosystems. The potential impacts these substances may have are currently underestimated due to the lack in available concentrations that lie below the limit of quantification (LOQ) for an important set of micropollutants. Here, the potential impacts due to 261 organic micropollutants on human health and aquatic environments were investigated at the scale of France. Even with concentrations below the LOQ, certain micropollutants were found to have a significant potential impact. For unmeasured concentrations, a global concentration distribution built from several datasets with different LOQ was used. By disregarding the unmeasured micropollutants, the potential impacts have been underestimated by >300 % on both human health and aquatic environments. Certain substances, such as hydrazine, endrin, or 2,3,7,8-TetraCDD, could lead to very strong potential impacts, even with unmeasured concentration levels. Moreover, the usual convention of LOQ/2 to replace unmeasured concentrations also appeared to overestimate the potential impact. The present work can be adapted to any other compartment or geographical context.

Towards a global multi objective optimization of wastewater treatment plant based on modeling and genetic algorithms.

The optimization of the Benchmark Simulation Model 1 (BSM1) through a multi objective genetic algorithm (MOGA) is studied in this paper. First, the optimization of the set points of the two Proportional Integral (PI) controllers proposed in BSM1 is performed. Then, a new controller layout composed of three PI controllers is proposed and the set points are also optimized. Among all performance indexes proposed in BSM1, only the effluent quality and the energy consumption for pumping and aeration were taken into account in both optimization problems. Since these two objectives are conflicting, the use of the MOGA allows in both cases a direct visualization of the possible trade-offs through a Pareto curve. These two case studies showed the feasibility of such optimizations even when dealing with computing intensive model like the full scale waste water treatment plant (WWTP) model.

A fuzzy-logic-based controller for methane production in anaerobic fixed-film reactors.

The main objective of this work was to develop a controller for biogas production in continuous anaerobic fixed-bed reactors, which used effluent total volatile fatty acids (VFA) concentration as control input in order to prevent process acidification at closed loop. To this aim, a fuzzy-logic-based control system was developed, tuned and validated in an anaerobic fixed-bed reactor at pilot scale that treated industrial winery wastewater. The proposed controller varied the flow rate of wastewater entering the system as a function of the gaseous outflow rate of methane and VFA concentration. Simulation results show that the proposed controller is capable to achieve great process stability even when operating at high VFA concentrations. Pilot results showed the potential of this control approach to maintain the process working properly under similar conditions to the ones expected at full-scale plants.

Combining pH and electrical conductivity measurements to improve titrimetric methods to determine ammonia nitrogen, volatile fatty acids and inorganic carbon concentrations.

Volatile fatty acids (VFA), inorganic carbon (IC) and total ammonia nitrogen (TAN) are key variables in the current context of anaerobic digestion (AD). Accurate measurements like gas chromatography and infrared spectrometry have been developed to follow the concentration of these compounds but none of these methods are affordable for small AD units. Only titration methods answer the need for small plant monitoring. The existing methods accuracy was assessed in this study and reveals a lack of accuracy and robustness to control AD plants. To solve these issues, a new titrimetric device to estimate the VFA, IC and TAN concentrations with an improved accuracy was developed. This device named SNAC (System of titration for total ammonia Nitrogen, volatile fatty Acids and inorganic Carbon) has been developed combining the measurement of electrical conductivity and pH. SNAC were tested on 24 different plant samples in a range of 0-0.16 mol.L(-1) TAN, 0.01-0.21 mol.L(-1) IC and 0-0.04 mol.L(-1) VFA. The standard error was about 0.012 mol.L(-1) TAN, 0.015 mol.L(-1) IC and 0.003 mol.L(-1) VFA. The coefficient of determination R(2) between the estimated and reference data was 0.95, 0.94 and 0.95 for TAN, IC and VFA respectively. Using the same data, current methods based on key pH points lead to standard error more than 14.5 times higher on VFA and more than 1.2 times higher on IC. These results show that SNAC is an accurate tool to improve the management of AD plant.

A hybrid cascade control scheme for the VFA and COD regulation in two-stage anaerobic digestion processes.

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 110days. 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.

Use of fermentative metabolites for heterotrophic microalgae growth: Yields and kinetics.

The growth of two lipid-producing Chlorella species on fermentative end-products acetate, butyrate and lactate, was investigated using a kinetic modeling approach. Chlorella sorokiniana and Auxenochlorella protothecoides were grown on synthetic media with various (acetate:butyrate:lactate) ratios. Both species assimilated efficiently acetate and butyrate with yields between 0.4 and 0.5g carbon of biomass/g carbon of substrate, but did not use lactate. The highest growth rate on acetate, 2.23d(-1), was observed for C. sorokiniana, and on butyrate, 0.22d(-1), for A. protothecoides. Butyrate removal started after complete acetate exhaustion (diauxic effect). However, butyrate consumption may be favored by the increase of biomass concentration induced by the initial use of acetate. A model combining Monod and Haldane functions was then built and fitted the experimental data well for both species. Butyrate concentration and (acetate:butyrate) ratios were identified as key parameters for heterotrophic growth of microalgae on fermentative metabolites.

First step towards a fast analytical method for the determination of Biochemical Methane Potential of solid wastes by near infrared spectroscopy.

Methane can be produced by anaerobic digestion. The Biochemical Methane Potential (BMP) test is widely applied to determine the anaerobic biodegradability of wastes. It is based on a fermentation process, which is time consuming, about 30 days. This study investigates the use of near infrared spectroscopy to predict the Biochemical Methane Potential value of municipal solid waste. Near infrared spectroscopy has the advantage to be very fast and applicable to solid waste with a light sample preparation. Satisfying results were obtained: R(2)=0.76; Standard Error of Prediction=28 ml CH(4) g(-1) VS, that compare very favourably with reported results for other more expensive and more time-consuming methods. To our knowledge, it is the first time near infrared spectroscopy is used to predict the Biochemical Methane Potential value. Using near infrared spectroscopy for waste management would thus lead to a real benefit from an industrial point of view.

Identification of interacting mixed cultures of lactic acid bacteria by their exclusion from a model predicting the acidifying activity of non-interacting mixed cultures.

A model predicting the acidifying activity of mixed cultures of lactic acid bacteria and based on the lack of interaction between the strains has been investigated to identify interacting cultures. Three mixed cultures with Streptococcus thermophilus TH3 and ST7 and Lactobacillus delbrueckii ssp. bulgaricus LB10 were grown on milk. The acidifying activities of the two mixed cultures TH3/LB10 and TH3/ST7 were predicted accurately by the model, with mean prediction errors of 7.7% and 14.1%, respectively. However, the model underestimated the acidifying activity of the mixed culture ST7/LB10, with a mean prediction error of 43.5%, which provides evidence of positive interaction between the strains ST7 and LB10 during acidification.

Indirect measurement of water content in an aseptic solid substrate cultivation pilot-scale bioreactor.

A lack of models and sensors for describing and monitoring large-scale solid substrate cultivation (SSC) bioreactors has hampered industrial development and application of this type of process. This study presents an indirect dynamic measurement model for a 200-kg-capacity fixed-bed SSC bioreactor under periodic agitation. Growth of the filamentous fungus Gibberella fujikuroi on wheat bran was used as a case study. Real data were preprocessed using previously reported methodology. The model uses CO2 production rate and inlet air conditions to estimate average bed water content and average bed temperature. The model adequately reproduces the evolution of the average bed water content and can therefore be used as an on-line estimator in pilot-scale SSC bioreactors. To obtain a reasonable fit of the bed temperature, however, inlet air humidity measurements will have to be adjusted with a data reconciliation algorithm. Good estimation of temperature is important for the future design of improved water content estimation using state observers. The model also provides insight into understanding the complex behavior of the dynamic system, which could prove useful when establishing advanced model-based operational and control strategies.

Effect of citrate on growth of Lactococcus lactis subsp. lactis in milk.

The effect of citrate on the growth of Lactococcus lactis subsp. lactis var. diacetylactis in milk has been investigated. Five strains of Lactococcus lactis subsp. lactis var. diacetylactis were compared to their citrate-negative variants, which lack the plasmid coding for citrate permease. In most cases, acidification kinetics and the final bacterial concentration of pure cultures of parental and variant strains did not differ significantly. Co-cultures of parental and variant strains, however, systematically tended towards the predominance of parental strains. Citrate metabolism is responsible for this change, since the predominance of citrate-positive strains was not observed in the absence of citrate. Continuous culture in milk enabled the difference in growth rates between the parental strain Lactococcus lactis subsp. lactis var. diacetylactis CDI1 and its citrate-negative variant to be quantified by following changes in the populations of the two co-cultured strains. At 26 degrees C, the growth rate of the parental strain was 7% higher than that of its citrate-negative variant. These results show that citrate metabolism slightly stimulates the growth of lactococci in milk.

On-line estimation of biological variables during pH controlled lactic acid fermentations.

Indirect measurement of lactose, galactose, lactic acid, and biomass concentration from on-line sodium hydroxide weight measurements have been obtained for pure and mixed batch cultures of Streptococcus salivarius ssp. thermophilus 404 and Lactobacillus delbrueckii subsp. bulgaricus 398 conducted at controlled pH and temperature. Linear correlations were established between the equivalent sodium hydroxide concentration and the lactose (substrate), galactose and lactic acid (products) concentrations while nonlinear relationships were developed between biomass and lactic acid concentrations. These nonlinear relationships took into account the inhibitory effect of lactic acid on growth and acidification. The indirect measurements of biomass concentration were introduced into a nonlinear estimator of the state variables and of the specific growth and lactic acid production rates. Good agreement was found between estimated and measured biomass concentrations (error index ranging from 10.8% to 12.6%). The results showed the feasibility of on-line estimation of biomass concentration and of the specific kinetics from NaOH addition weight measurements and its applicability for monitoring lactic acid fermentations. Using off-line measurements of L(+) and D(-) lactic acid concentrations, the evolution of the concentration of each strain in mixed cultures was obtained from the relationships proposed for the mixed cultures. (c) 1994 John Wiley & Sons, Inc.

Deacidification by Debaryomyces hansenii of smear soft cheeses ripened under controlled conditions: relative humidity and temperature influences.

Model smear soft cheeses were prepared from pasteurized milk inoculated with Debaryomyces hansenii (304, GMPA) and Brevibacterium aurantiacum (ATCC 9175) under aseptic conditions. Debaryomyces hansenii growth and curd deacidification were studied in relation to ripening chamber temperature and relative humidity (RH). A total of 9 descriptors, mainly based on kinetic data, were defined to represent D. hansenii growth (2 descriptors), cheese deacidification (5 descriptors), and cheese ripening (2 descriptors). Regardless of the temperature, when the RH was 85%, D. hansenii growth was inhibited due to limitation of carbon substrate diffusions; consequently, cheese deacidification did not take place. Debaryomyces hansenii growth was most prolific when the temperature was 16 degrees C, and the RH was 95%. Kinetic descriptors of lactate consumption and pH increase were maximal at 16 degrees C and 100% RH. Under these 2 ripening conditions, on d 14 (packaging) the creamy underrind represented a third of the cheese; however, at the end of ripening (d 42), cheese was too liquid to be sold. Statistical analysis showed that the best ripening conditions to achieve an optimum between deacidification and appearance of cheeses (thickness of the creamy underrind) were 12 degrees C and 95 +/- 1% RH.