Microbial analysis in biogas reactors suffering by foaming incidents.

scientific article published on 28 May 2014

Microbial analysis in biogas reactors suffering by foaming incidents. is …
instance of (P31):
scholarly articleQ13442814

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P356DOI10.1016/J.BIORTECH.2014.05.080
P698PubMed publication ID24968108
P5875ResearchGate publication ID263433189

P50authorDavide De FrancisciQ30539709
Irini AngelidakiQ41804134
Laura TreuQ42775940
Panagiotis G. KougiasQ55835136
Stefano CampanaroQ56573665
P407language of work or nameEnglishQ1860
P921main subjectbiogasQ171076
P304page(s)24-32
P577publication date2014-05-28
P1433published inBioresource TechnologyQ2120036
P1476titleMicrobial analysis in biogas reactors suffering by foaming incidents.
P478volume167

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cites work (P2860)
Q58418156Bacterial production of biosurfactants under microaerobic and anaerobic conditions
Q57825742Counteracting foaming caused by lipids or proteins in biogas reactors using rapeseed oil or oleic acid as antifoaming agents
Q33639356Foam-forming bacteria in activated sludge effectively reduced by rotifers in laboratory- and real-scale wastewater treatment plant experiments
Q104748232Identification of microorganisms responsible for foam formation in mesophilic anaerobic digesters treating surplus activated sludge
Q42653075Investigation of foaming causes in three mesophilic food waste digesters: reactor performance and microbial analysis
Q31042487Metagenomic analysis and functional characterization of the biogas microbiome using high throughput shotgun sequencing and a novel binning strategy
Q93185617Methods for quantification of growth and productivity in anaerobic microbiology and biotechnology
Q36220376Microbial community changes in methanogenic granules during the transition from mesophilic to thermophilic conditions
Q40464950Microbial population dynamics in urban organic waste anaerobic co-digestion with mixed sludge during a change in feedstock composition and different hydraulic retention times.
Q48130454Taxonomy of anaerobic digestion microbiome reveals biases associated with the applied high throughput sequencing strategies

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