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Swine effluents must be correctly handled to avoid negative environmental impacts. In this study, the profiles of two swine manure treatment systems were evaluated: a solid-liquid separation step, followed by an anaerobic reactor, and an aerobic step (System 1); and a biodigester followed by serial lagoons (System 2). Both systems were described by the assessment of chemical, bacterial and viral parameters. The results showed that in System 1, there was reduction of chemicals (COD, phosphorus, total Kjeldhal nitrogen - TKN - and NH(3)), total coliforms and Escherichia coli; however, the same reduction was not observed for Salmonella sp. Viral particles were significantly reduced but not totally eliminated from the effluent. In System 2, there was a reduction of chemicals, bacteria and viruses with no detection of Salmonella sp., circovirus, parvovirus, and torque teno virus in the effluent. The chemical results indicate that the treated effluent can be reused for cleaning swine facilities. However, the microbiological results show a need of additional treatment to achieve a complete inactivation for cases when direct contact with animals is required.

Appropriate enrichment of anaerobic microorganism's consortium is crucial for accurate biochemical methane potential (BMP) assays. An alternative method to produce and maintain a mesophilic methanogenic inoculum was demonstrated. Three sources of inoculum were mixed and acclimated for 857days in order to reach steady conditions (pH=7.90±0.46; VS/TS>50%; VFA/alkalinity=0.16±0.04gAcetic Acid/ [Formula: see text] ). Biogas yield >80% was obtained after 70days of inoculum acclimation in comparison to standard cellulose (>600mLN/gVS). Methanogen community analysis based on 16S rDNA of the inoculum revealed Archaea concentration of 3×10(12) gene copies/g (Methanobacteriales 8×10(10); Methanomicrobiales 8×10(10); and Methanosarcinales 4×10(11) gene copies/g). The proposed method for development and maintenance of microorganism enrichment inoculum demonstrates consistent BMP data which is a requirement for dependable prediction of biogas production at field scale operations.