Active prokaryotic population dynamics exhibit high correlation to reactor performance during methane production from acid hydrolysates of Agave tequilana var. azul bagasse.

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.

Impact of storage conditions on fungal community composition of green coffee beans Coffea arabica L. stored in jute sacks during 1 year.

AIMS: The purpose of this study was to evaluate the effect of warehouse storage conditions on the composition of the fungal community of green coffee beans (GCB) that were stored in jute sacks for 1 year. METHODS AND RESULTS: Molecular characterization of the fungal community composition and population dynamics obtained by Q-PCR, CE-SSCP (Simpson's diversity index D) and Illumina MiSeq sequencing indicated that Saccharomycetales dominated during the first 6 months of storage period with species as Meyerozyma guilliermondii and Pichia kluyveri. However, after 6 months of storage, the filamentous genus Wallemia became dominant. Principal components analysis correlated this fungal dynamic with storage conditions and other variables as chromaticity (colour), water activity, moisture content, reducing sugars concentration, fungal infection and ochratoxin A production. CONCLUSIONS: This study demonstrated that GCB stored in jute sacks after 6 months of storage lead to fungal population dynamics, decreased chromaticity in GCB by bleaching and, then, affected overall quality. SIGNIFICANCE AND IMPACT OF THE STUDY: Storage plays an important role in the quality evolution during the handling of the GCB. In this context, the composition of the microbial community could be considered a marker to assess the trade value of the coffee beans.

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.

Anaerobic treatment of tequila vinasses under seasonal operating conditions: start-up, normal operation and restart-up after a long stop and starvation period.

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.

Neural network modeling of the light profile in a novel photobioreactor.

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.