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Record W2976331814 · doi:10.5539/jas.v11n17p57

Nutrient Dynamics of an Aquaponic System in Southern Thailand

2019· article· en· W2976331814 on OpenAlexvenueno aff
Somsak Maneepong

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInnovations in Aquaponics and Hydroponics Systems
Canadian institutionsnot available
FundersWalailak UniversityThailand Research Fund
KeywordsAquaponicsAnimal scienceNutrientNile tilapiaHydroponicsAlkalinityOreochromisChemistryFish farmingAquacultureBiologyFish <Actinopterygii>FisheryAgronomyEcology

Abstract

fetched live from OpenAlex

Aquaponics is an integrated system of recirculation aquaculture and soilless culture that mainly aims to reduce water requirements, reduce waste discharge and maximize nutrient use. In the present study, an aquaponic system consisting of a 500 L fish tank, sedimentation and pH control tank, degassing tank and three vegetable growing beds was assembled and tested for 17 weeks. Fifty Nile tilapias (Oreochromis niloticus) were reared and fed thrice daily with a complete diet containing 32% protein. Buffer of solid rocks (dead corals) were installed for pH control. Water convolvulus (Ipomoea aquatica) and Tokyo Bekana (Brassica rapa) were rotationally grown at different growth stages. Water samples were collected once a week to analyze pH and NH3/NH4+, NO3-, H2PO4-/HPO42-, SO42-, K, Na, Ca, Mg and Fe concentrations. Fish weight increased from 50 g/fish at the beginning of the experiment to 228 g/fish after 15 weeks. Water pH increased from 6.0 before rearing to 7.0 on the 4th week and varied over the range of 6.9 to 7.0 until the end of the experiment without any additional acid or alkali. Total NH3/NH4+ increased to 10.2 mg-N/L on the 2nd week and rapidly declined to levels below 2.0 mg-N/L. Phosphate, SO42-, Na and Mg accumulated in the system, whereas Ca gradually increased and reached equilibrium at 47&amp;plusmn;2 mg/L. K and NO2-/NO3- varied considerably at concentrations lower than the general requirement of the vegetables. The first crops of vegetables initially grew well, but growth rates declined remarkably and latter crops showed complex nutrient deficiency. The system could be maintained for 17 weeks without waste discharge.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.910
Threshold uncertainty score0.149

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.008
GPT teacher head0.212
Teacher spread0.203 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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