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Record W3161785749 · doi:10.5539/eer.v11n1p37

Characterization of the Microbial Community in A Continuous Garbage Treatment Process

2021· article· en· W3161785749 on OpenAlexvenueno aff
Satoshi Matsuda, Reni Sutri Suherman, Akira Yanagihara, Tadashi Yamauchi

Bibliographic record

VenueEnergy and Environment Research · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicComposting and Vermicomposting Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsGarbageAerationOrganic matterMicrobial population biologyProcess (computing)DecompositionGarbage collectionProcess engineeringPulp and paper industryEnvironmental scienceBiochemical engineeringWaste managementComputer scienceEcologyBiologyEngineeringBacteria

Abstract

fetched live from OpenAlex

Previously, we developed a “static type” garbage treatment system whose performance exceeds that of conventional garbage treatment systems. However, we could not explain the system’s excellent performance especially from a microbial ecosystem’s stand point (Matsuda et al, 2017). Microbial activity causes the decomposition of organic materials in a garbage treatment process. However, we do not know which microbes are effective in garbage decomposition and what relationship exists between the succession of a microbial community and the decomposition of organic materials in a garbage composting process.  This study analyzed the relationship between a continuous operation garbage treatment system’s microbial community and the decomposition of organic matter and evaluated for effective microbes in the same garbage treatment system. Although many research articles have been published on the composting processes throughout the world, most of them employ batch processes and not continuous processes. Conversely, most real-world practical composting plants adopt a continuous operation system in which fresh feed is usually input once a day with continuous aeration and intermittent mixing.  To comprehensively analyze the microbial community, three different approaches were adopted in this study; 1) colony observation, 2) DNA analysis, and 3) the enzymatic activities of each colony. In our experiment, the working volume was 10 L of leaf mold and 40 g/(day L) of garbage (the organic load) was input to the reactor every day at a fixed time. Dog food with 70 % moisture content was used as a model garbage substrate. The reactor’s internal temperature, the total reactor’s weight and the sampled residue’s weight, moisture content and pH were measured before inputting garbage. Additionally, the reactor’s internal temperature was measured six hours later. The internal temperature was about 55 ℃ at the highest without heating. The organic matter decomposition rate was about 50 % and the weight reduction rate was over 90 %, implying successful garbage decomposition was achieved. The microbial composition and the number of the colonies seen on the medium plate changed every day and did not realize a “steady state.” Thus an extremely efficient microbe does not exist. Only eleven microbes were isolated; yet many more microbes must exist in the system but were not counted due to a high dilution rate. From our DNA analysis, the PCR-DGGE profile of the microbial community in the garbage residue showed that bands of isolated colonies were detected in the same positions as the bands of garbage residue, which contained all kinds of microbes. Nine microbes were identified using 16S rRNA genome from eleven isolated ones. The identified microbes were of different bacterial species and their characteristics were examined from the stand point of nutritional property and enzymatic activity.  The garbage decomposition process consists of two steps, solubilization and metabolization. Extracellular enzymes act during solubilization of solid garbage residue, and intracellular enzymes work when water-soluble substances are taken up into bacterial cells and metabolized. Protease and amylase activity were measured to assess extracellular enzymatic activity and dehydrogenase activity was measured to evaluate intracellular enzymatic activity. The enzyme activities of bacterial strains significantly differed by strain. Results from this study suggest complementary microbial activity and that Bordetella trematum, Bacillus cereus, Bacillus subtills subtills and Streptomyces thermocarboxydus effectively decompose garbage.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.153

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.271
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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