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Record W4391426466 · doi:10.1016/j.isci.2024.109073

Inoculum and pH effects on ammonium removal and microbial community dynamics in aquaponics systems

2024· article· en· W4391426466 on OpenAlexafffund
Peyman Derikvand, Brittany Sauter, B. A. Keddie, Lisa Y. Stein

Bibliographic record

VenueiScience · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInnovations in Aquaponics and Hydroponics Systems
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta InnovatesAlberta Innovates Bio Solutions
KeywordsAquaponicsAmmoniumChemistryEnvironmental chemistryNitriteNitrificationMicroorganismAmmoniaMicrobial population biologyNitrateBacteriaNitrogenBiologyBiochemistry

Abstract

fetched live from OpenAlex

Understanding the ecology of microorganisms is essential for optimizing aquaponics systems. Effects of pH and inoculum on ammonium removal and dynamics of microbial community composition from all compartments of lab-scale aquaponics systems were examined. Initial ammonium accumulation in systems with comammox-enriched inocula were 47% and 69% that of systems enriched with ammonia-oxidizing bacteria (AOB), with higher rates of ammonium removal and transient nitrite accumulation measured in the latter systems. By the end of operation, Nitrosomonas and Nitrosospira AOB were dominant nitrifiers in systems at pH 7.6–7.8, whereas comammox ( Nitrospira ) nitrifiers and plant growth-promoting microbes were abundant in systems operating at pH 5.8–6.0. Lower pH systems supported more robust plant growth with no significant effects on fish health. This study demonstrated functional redundancy of aquaponics microbiota, with selectivity of nitrifying taxa as a function of pH. The results suggest that inoculum and pH are important considerations for aquaponics system initiation and optimization.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.812
Threshold uncertainty score0.404

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.234
Teacher spread0.221 · 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 designSimulation or modeling
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

Citations8
Published2024
Admission routes2
Has abstractyes

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