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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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

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 head0.028
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 source (direct Gemma or distilled Codex), 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

Citations4
Published2014
Admission routes1
Has abstractyes

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Same venueEnvironment and Natural Resources ResearchSame topicHeavy metals in environmentFrench-language works237,207