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Record W2121573269 · doi:10.5539/enrr.v4n2p39

Bioaccumulation of Cadmium in Siam (Chromolaena odorata) and Node (Synedrella nodiflora) Weeds: Impact of Ethylene Diamine Tetraacetic Acid (EDTA) on Uptake

2014· article· en· W2121573269 on OpenAlexvenueno aff
Afamefuna Elvis Okoronkwo, Ademola Festus Aiyesanmi, A. C. Odiyi, Michael Oluwatoyin Sunday, I. Shoetan

Bibliographic record

VenueEnvironment and Natural Resources Research · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsnot available
Fundersnot available
KeywordsChromolaena odorataShootCadmiumPhytoremediationBioaccumulationAmendmentChemistrySoil waterHorticultureSoil contaminationWeedBotanyEnvironmental chemistryHeavy metalsBiology

Abstract

fetched live from OpenAlex

The translocation and accumulation of Cd by Synedrella nodiflora and Chromolaena odorata plants growing in artificially Cd-contaminated soils amended with EDTA or without amendment had been studied to assess the phytoremediation potential of both species. Results showed that roots of S. nodiflora had the capacity of taking up a maximum 86.2 mg/kg of Cd from the contaminated soil while concentration in shoots amounts to a maximum 73.8 mg/kg. C. odorata was able to accumulate 42.8 mg/kg and 33.8 mg/kg in its roots and shoots respectively. The mobility of soil cadmium and the concentration of Cd in plants were both increased by EDTA amendment. EDTA application facilitated the translocation of Cd since the concentration in the roots and shoots of S. nodiflora increased to 104.9 mg Cd/kg and 77.0 mg Cd/kg respectively although the amendment effect was more pronounced on C. odorata increasing from 42.8 mg Cd/kg in roots from non-amended soils to 83.7 mg Cd/kg in the roots from amended soils. Despite the improved uptake by C. odorata, S. nodiflora appears to be more suitable for phytoremediation of Cd contaminated soils.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.659
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.028
GPT teacher head0.319
Teacher spread0.291 · 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 designObservational
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

Citations4
Published2014
Admission routes1
Has abstractyes

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