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Record W4409667324 · doi:10.3390/soilsystems9020038

Biochar Amendment in Remediation of Heavy Metals in Paddy Soil: A Case Study in Nobewam, Ghana

2025· article· en· W4409667324 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSoil Systems · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsBiocharAmendmentEnvironmental remediationHeavy metalsEnvironmental scienceSoil remediationSoil contaminationWaste managementEnvironmental protectionEnvironmental chemistrySoil waterContaminationChemistrySoil scienceLawEngineeringPolitical scienceEcologyBiology

Abstract

fetched live from OpenAlex

Biochar is a stabilised, carbon-rich material created when biomass is heated to temperatures usually between 450 and 550 °C, under low-oxygen concentrations. This study evaluated the effectiveness of sawdust, cocoa pod ash and rice husk biochars in remediating metal-contaminated paddy soil in Nobewam, Ghana. Biochar was applied 21 days before cultivating the rice for 120 days, followed by soil sampling and rice harvesting for metals and physicochemical analyses. Compared to the untreated soils, biochar treatments exhibited an enhancement in soil quality, characterised by an increase in pH of 1.01–1.20 units, an increase in available phosphorus (P) concentration of 6.76–13.05 mg/kg soil and an increase in soil total nitrogen (N), and organic carbon (OC) concentration, ranging from 0.02% to 0.12%. Variabilities in electrical conductivity and effective cation exchange capacity were observed among the treated soils. Concentrations of potentially toxic metals (arsenic, cadmium, copper, mercury, lead and zinc) in paddy soils and rice analysed by atomic absorption spectroscopy showed significant differences (p < 0.05) among the sampled soils. The concentrations of arsenic and lead in all soil samples exceeded the Canadian Council of Ministers of the Environment soil quality guideline for agricultural soils, with untreated soils having the highest levels among all the soils. Cadmium had a potential ecological risk index > 2000 and a geoaccumulation index above 5, indicating pollution in all samples. In contrast, arsenic and mercury contamination were only found in the untreated soils. Among the tested treatments, rice husk and its combinations, particularly with cocoa pod ash, showed significant efficacy in reducing metal concentrations in the soils. The potential non-carcinogenic human health risks associated with the consumption of rice grown in biochar-treated soils were lower for all the metals compared to the control samples. Future research should focus on long-term field studies to validate these findings and explore the underlying mechanisms governing metal immobilization in paddy fields.

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.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.019
GPT teacher head0.275
Teacher spread0.256 · 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