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Record W3112024325 · doi:10.5539/jas.v13n1p122

Assessment of Soil Fertility and Crop Nutrient Status in Agricultural Soils Near a Brick Kiln Cluster

2020· article· en· W3112024325 on OpenAlexvenueno aff
Nasrin Chowdhury, Md. Mamunur Rasid

Bibliographic record

VenueJournal of Agricultural Science · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsnot available
FundersUniversity Grants Commission
KeywordsEnvironmental scienceSoil waterBrickSoil fertilityKilnFertilizerNutrientAgricultureAgronomySoil scienceGeographyWaste managementEcologyBiologyEngineering

Abstract

fetched live from OpenAlex

Brick kiln exhaust when deposited can hamper the nutritional status of the agricultural soils and crops. To study the impact, soil and associated plant samples were collected from the vicinity of a brick kiln cluster in Chattogram, Bangladesh. The soil contamination was evaluated by heavy metal indices. Agricultural soils close to the brick kiln area were very strongly acid to slightly acid. Organic carbon, total nitrogen and available phosphorus content of the agriculture soils near brick kiln cluster were 0.35% to 1.01%, 0.10 to 0.24% and 2.21 to 13.48 mg kg-1 respectively and the significant different mean value of 0.70%, 0.22% and 14.65 mg kg-1 respectively in the reference soil. The nutritional status of sampling sites was lower than the previously reported data. The nutrition status of the plants was at an optimum level as regular fertilizer application was practiced but showed an irregular pattern along with all the soil parameters and heavy metal indices. The contamination factor (Cd), potential ecological risk index (PER) and geo-accumulation index (Igeo) demonstrated that the agricultural soils in the vicinity of the brick kiln cluster were moderately- to highly-polluted. This indicates the deterioration of soil quality by uncontrolled brick kiln operation.

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)0.001
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 score0.605
Threshold uncertainty score0.432

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.013
GPT teacher head0.251
Teacher spread0.237 · 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
Published2020
Admission routes1
Has abstractyes

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