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Treated effluent, soil and vegetable samples were analyzed for nutrient, physicochemical, Cr and microbial parameters using standard methods (APHA).
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Furthermore the alterations of commonly used microbial parameters to monitor the process, such as richness, evenness and diversity indices were unsuccessful to predict the process failure.
The associations between the selected home characteristics and microbial parameters in mattress dust were assessed using linear mixed models, using random effects.
Microbial parameters were determined from respiration measurements using an automated respirometer based on electrolytic oxygen microcompensation [38] in fresh soil samples equivalent to 3.5 g dry weight.
Differences in microbial parameters between the study groups were analysed using ordinal regression.
A total of 132 isolates were collected from the plates used to enumerate the microbial parameters mentioned above.
Associations between microbial parameters and the asthma score and lung function were examined using mixed negative binomial regression and linear mixed models, respectively.
Microbial parameters were determined by a substrate-induced respiration method (Anderson and Domsch1978) using an automated respirometer based on electrolytic O2 microcompensation (Scheu1992).
The retrospective management [ 6] of our reactors showed that traditional microbial parameters such as richness, diversity and evenness which could be potentially used to predict process imbalances were not effective, due to the differential behaviours of microbial consortia in the replicated reactors.
Soil samples were characterized for their physicochemical and microbial parameters according to standard methods.
However, endotoxin will be included, investigating the correlation between different microbial parameters.
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