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Record W2990039628 · doi:10.9734/ajbgmb/2019/v2i330063

Contamination of Tributyltin Compounds on Shellfish Uses Tolerable Average Residue Levels on Pulau Pramuka Kepulauan Seribu

2019· article· en· W2990039628 on OpenAlexaboutno aff
Seali Lismaryanti, Zahidah Zahidah, Asep Sahidin, Herman Hamdani

Bibliographic record

VenueAsian Journal of Biochemistry Genetics and Molecular Biology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and Coastal Ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsTributyltinShellfishPerna viridisContaminationFisheryBiologyEnvironmental chemistryEnvironmental scienceEcologyAquatic animalMusselChemistryFish <Actinopterygii>

Abstract

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Aims: This research is aimed to know the contamination of tributyltin (TBT) compounds on shellfish uses TARL. To determine the level of contamination in seafood, shellfish use the weight of an average person.&#x0D; Place and Duration of Study: Ecology Laboratory and Central Laboratory, Padjadjaran University from January until April 2019.&#x0D; Methodology: The research was conducted purposive sampling consisted of 3 different location with a total 98 shell. Tributyltin analysis is to determine the level of tributyltin contamination in shellfish which can affect an individual in consuming tributyltin-contaminated shells. The results were statistically analyzed TARL carried out and analyzed descriptively.&#x0D; Results: 8 species of shellfish have been identified, Tellina virgata, Perna viridis, Anadara granosa, Anadara antiquata, Fragum unedo, Fimbria fimbricata, Gafrarium tumidum and Tridacna squamosa. The number of bivalves found was different at each station. The total number of shells identified in all 98 individuals from the three stations, Anadara granosa species is the dominant species found, this is because Anadara granosa shells can live in different types of habitats and their existence tends to dominate the open, coastal and estuary waters. The results of tributyltin analysis on shellfish showed TBT contamination in shellfish, each research location found different concentrations of tributyltin. Muara Angke pier was found to be the highest TBT concentration in meat in Perna viridis at 0.170 ± 0.0192 ng.g-1. From available TBT analysis data, the estimated daily TBT intake to the average person who likes seafood on Pramuka Island with a bodyweight of 60 kg is 0.54-10.2 ng TBT.person-1.day-1 through shellfish consumption. Although this value is still far from the threshold of a tolerable value of 15 g.person-1.day-1. The estimated daily intake of TBT through seafood products in Indonesia is among the lowest compared to developed countries, such as Japan (3000-100000 g.person-1.day-1), Canada (&lt;610-15000 g.person-1.day-1), USA (4000-45000 g.person-1.day-1), Finland (970-9700 g.person-1.day-1) and some Asian countries such as Thailand (228-45714 through shellfish consumption and the Philippines (2361-68312 through shellfish). Several things that affect daily consumption per capita in determining TARL are based on average values. This implies, that some populations consume more seafood products (fishermen, people who have a preference for consuming fish) than the average so that there is a greater risk of seafood that has been contaminated with tributyltin. Then TARL is based on the average person weighing 60 kg. A person with a lighter weight will receive relatively more compound tributyltin per kg of body weight.&#x0D; Conclusion: Based on the results of the research is the contamination of tributyltin compounds in shellfish seafood by 0.170 ng.g-1 with an estimated daily intake of TBT to the average person who likes seafood on Pramuka Island with a bodyweight of 60 kg is 0.54-10.2 ng TBT.person-1.day-1 through shellfish consumption.

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 score0.012
Threshold uncertainty score0.485

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 head0.005
GPT teacher head0.223
Teacher spread0.217 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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