Phyto-extraction of Copper, Iron, Manganese, and Zinc from Environmentally Contaminated Sites in Ethiopia, with Three Grass Species
Bibliographic record
Abstract
Abstract Rhodegrass (Chloris gayana cv. Kallide) and forage setaria (Setaria sphacelata cv. Kazungula), two indigenous grass species, and oat (Avena sativa L.), a recently introduced forage crop, were grown on contaminated sites in Ethiopia, to determine their potential in removing copper (Cu), iron (Fe), manganese (Mn), and zinc (Zn) from the soils. Soil pH influenced the availability and plant uptake of micronutrients; therefore, the grasses grown at the industrial waste site with a high pH, had the lowest micronutrient concentrations. Setaria and rhodesgrass had higher concentrations of all the micronutrient metals than oat. Rhodesgrass and setaria accumulated concentrations of Fe and Mn, normally considered toxic to many crops, without developing chlorotic symptoms and yield suppressions. Iron in setaria and Zn in rhodesgrass declined significantly with advancing maturity. Considering biomass yield and tissue concentration, it was found that setaria removed the greatest quantity of micronutrients per unit area of soil. Keywords: PhytoextractionIndustrial wasteMunicipal wastesIndigenous speciesEthiopia Acknowledgments We acknowledge the ESTC (Ethiopian Science and Technology Commission) and ENDA (Environment Development Action) Ethiopia, for covering the field expenses in Ethiopia. The interest, cooperation and support given by Mr. Camille de Stoop, the country coordinator of ENDA, made the field work a success. Special thanks goes to W/o Amakelech Bogale, from ENDA Ethiopia, for providing unreserved technical assistance during the field work. We are very thankful to Mrs. Gisele Morin-Labatut, who facilitated support from IDRC to cover travel cost and part of the laboratory expenses. The ILRI is acknowledged for supplying the planting materials and for the weather data. We are also very grateful for access to facilities, and excellent cooperation by the Forage Crops Section of the Saskatoon Research Centre of Agriculture and Agri-Food Canada. The Department of Soil Science of the University of Saskatchewan is acknowledged for its support in some of the laboratory analyses and Mr. Barry Goetz for the analytical work.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".