Effect of the composting process on physicochemical properties and concentration of heavy metals in market waste with additive materials in the Ga West Municipality, Ghana
Bibliographic record
Abstract
The main objective of this study was to assess the physiochemical properties and phytotoxicity of compost made from different organic waste materials sourced from local markets. The Stack pile composting was carried out with market waste, sawdust, rice straw, and swine manure in four different combinations. Parameters such as temperature, pH, nitrogen, phosphorus, potassium, and heavy metal concentrations were monitored. Germination test with water extracts of the composts was done to assess phytotoxicity of the composts. All compost piles recorded temperatures of 38 °C slightly above the recorded ambient temperature of 34 °C at the start of composting. The pH value ranged from 7.12 to 8.2 for the different compost types. The total organic carbon and total nitrogen values ranged from 27.05–31.06 to 0.77–0.97%, respectively. The total phosphorus and total potassium values ranged from 0.2–1.87 to 0.39–2.3%, respectively, for different compost types. The C/N ratio values ranged from 29.09:1 to 36.22:1. All the composts had heavy metal concentrations below the Canadian Council of Ministers of the Environment standards. Germination indices, a measure of plant vs supporting potential, ranged from 80 to 99% for Solanum lycopersicum , 170 to 198% for Cucumis sativus , and 114 to 166% for Brassica oleracea . The study confirms the notion that composting municipal solid waste is a viable organic waste management strategy, and with the potential to enhance waste management system, while promoting cultivation of vegetables for food security.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".