RESUMEN
Inhibition of anaerobic digestion through accumulation of volatile fatty acids occasionally occurs as the result of unbalanced growth between acidogenic bacteria and methanogens. A fast recovery is a prerequisite for establishing an economical production of biogas. However, very little is known about the microorganisms facilitating this recovery. In this study, we investigated the organisms involved by a novel approach of mapping protein-stable isotope probing (protein-SIP) onto a binned metagenome. Under simulation of acetate accumulation conditions, formations of (13)C-labeled CO2 and CH4 were detected immediately following incubation with [U-(13)C]acetate, indicating high turnover rate of acetate. The identified (13)C-labeled peptides were mapped onto a binned metagenome for improved identification of the organisms involved. The results revealed that Methanosarcina and Methanoculleus were actively involved in acetate turnover, as were five subspecies of Clostridia. The acetate-consuming organisms affiliating with Clostridia all contained the FTFHS gene for formyltetrahydrofolate synthetase, a key enzyme for reductive acetogenesis, indicating that these organisms are possible syntrophic acetate-oxidizing (SAO) bacteria that can facilitate acetate consumption via SAO, coupled with hydrogenotrophic methanogenesis (SAO-HM). This study represents the first study applying protein-SIP for analysis of complex biogas samples, a promising method for identifying key microorganisms utilizing specific pathways.
Asunto(s)
Acetatos/metabolismo , Bacterias/aislamiento & purificación , Bacterias/metabolismo , Proteínas Bacterianas/metabolismo , Anaerobiosis , Bacterias/química , Bacterias/genética , Proteínas Bacterianas/química , Proteínas Bacterianas/genética , Biocombustibles/análisis , Isótopos de Carbono/metabolismo , Ácidos Grasos Volátiles/metabolismo , Marcaje Isotópico , Metagenómica , Metano/metabolismo , Oxidación-ReducciónRESUMEN
The feasibility of using a diffuse reflectance probe attached to a near infrared spectrometer to monitor the total ammonia nitrogen (TAN) content in an anaerobic digester run on cattle manure was investigated; as a previous study has indicated that this probe can be easily attached to an anaerobic digester. Multivariate modelling techniques such as partial least squares regression and interval partial least squares methods were used to build models. Various data pre-treatments were applied to improve the models. The TAN concentrations measured were in the range of 1.5 to 5.5 g/L. An R(2) of 0.91 with an RMSEP of 0.32 was obtained implying that the probe could be used for monitoring and screening purposes.
Asunto(s)
Amoníaco/análisis , Bacterias Anaerobias/metabolismo , Reactores Biológicos/microbiología , Técnicas Biosensibles , Fotometría/instrumentación , Espectroscopía Infrarroja Corta/instrumentación , Transductores , Diseño de Equipo , Análisis de Falla de EquipoRESUMEN
In this study two approaches to predict the total alkalinity (expressed as mg L(-1)HCO(3)(-)) of an anaerobic digester are examined: firstly, software sensors based on multiple linear regression algorithms using data from pH, redox potential and electrical conductivity and secondly, near infrared reflectance spectroscopy (NIRS). Of the software sensors, the model using data from all three probes but a smaller dataset using total alkalinity values below 6000 mg L(-1)HCO(3)(-) produced the best calibration model (R(2)=0.76 and root mean square error of prediction (RMSEP) of 969 mg L(-1)HCO(3)(-)). When validated with new data, the NIRS method produced the best model (R(2)=0.87 RMSEP=1230 mg L(-1)HCO(3)(-)). The NIRS sensor correlated better with new data (R(2)=0.54). In conclusion, this study has developed new and improved algorithms for monitoring total alkalinity within anaerobic digestion systems which will facilitate real-time optimisation of methane production.
Asunto(s)
Algoritmos , Bacterias Anaerobias/metabolismo , Metano/biosíntesis , Eliminación de Residuos/métodos , Programas Informáticos , Espectrofotometría Infrarroja/métodos , Bicarbonatos/análisis , Concentración de Iones de Hidrógeno , Modelos Lineales , Modelos TeóricosRESUMEN
A non-destructive and novel in situ acoustic sensor approach based on the sound absorption spectra was developed for identifying and classifying different seed types. The absorption coefficient spectra were determined by using the impedance tube measurement method. Subsequently, a multivariate statistical analysis, i.e., principal component analysis (PCA), was performed as a way to generate a classification of the seeds based on the soft independent modelling of class analogy (SIMCA) method. The results show that the sound absorption coefficient spectra of different seed types present characteristic patterns which are highly dependent on seed size and shape. In general, seed particle size and sphericity were inversely related with the absorption coefficient. PCA presented reliable grouping capabilities within the diverse seed types, since the 95% of the total spectral variance was described by the first two principal components. Furthermore, the SIMCA classification model based on the absorption spectra achieved optimal results as 100% of the evaluation samples were correctly classified. This study contains the initial structuring of an innovative method that will present new possibilities in agriculture and industry for classifying and determining physical properties of seeds and other materials.
Asunto(s)
Acústica/instrumentación , Técnicas Biosensibles/instrumentación , Semillas/clasificación , Sonido , Absorción , Análisis Multivariante , Análisis de Componente PrincipalRESUMEN
It is in the interest of operators of anaerobic digestion plants to maximise methane production whilst concomitantly reducing the chemical oxygen demand of the digested material. Although the production of biogas through anaerobic digestion is not a new idea, commercial anaerobic digestion processes are often operated at well below their optimal performance due to a variety of factors. This paper reviews current optimisation techniques associated with anaerobic digestion and suggests possible areas where improvements could be made, including the basic design considerations of a single or multi-stage reactor configuration, the type, power and duration of the mixing regime and the retention of active microbial biomass within the reactor. Optimisation of environmental conditions within the digester such as temperature, pH, buffering capacity and fatty acid concentrations is also discussed. The methane-producing potential of various agriculturally sourced feedstocks has been examined, as has the advantages of co-digestion to improve carbon-to-nitrogen ratios and the use of pre-treatments and additives to improve hydrolysis rates or supplement essential nutrients which may be limiting. However, perhaps the greatest shortfall in biogas production is the lack of reliable sensory equipment to monitor key parameters and suitable, parallelised control systems to ensure that the process continually operates at optimal performance. Modern techniques such as software sensors and powerful, flexible controllers are capable of solving these problems. A direct comparison can be made here with, for instance, oil refineries where a more mature technology uses continuous in situ monitoring and associated feedback procedures to routinely deliver continuous, optimal performance.