Availability of Three Phosphorus Fertilizers to Corn Grown in Limed Acid-Producing Mine Tailings
Bibliographic record
Abstract
Liming can modulate phosphorus (P) availability to plants growing in acid-forming media. The objectives of this study were to determine the effects of lime and phosphorus rates on corn (Zea mays L.) grown under greenhouse conditions on an acid-producing mine tailing, and to evaluate P desorption from the mine tailing after harvest. The acid-sulfide tailing (pH 2.65) collected from the Solbec-Cupra mine in Quebec was limed using CaCO3 to theoretical pH values of 5 (11 g/kg), 6 (17 g/kg) and 7 (30 g/kg) prior to corn production. Phosphorus was thoroughly mixed with the tailing at rates of 0, 22.4, 44.8 and 89.6 mg P/kg. Commercial peat-shrimp waste compost; a commercial bone flour fertilizer and reagent-grade KH2PO4 were used as P sources. Corn (Zea Mays L. cv. 'Pride 1122') was grown for 50 days after emergence. After harvest, the mean tailing pH values varied from 4.20 to 7.20. Dry matter yield of plant tops was significantly affected by lime and phosphorus treatments. Corn yields were significantly correlated with pH, salinity index (electrical conductivity of aqueous extracts) and ammonium acetate-extractable Ca and Mg. In all P treatments, the highest yield was obtained with plot receiving 44.8 mg P/kg and lime rate to achieve pH 6 (17 g of CaCO3/kg). In general, mineral composition of the tops did not show toxic accumulation of trace metals. The P extracted by Na2EDTA from some tailing samples was a time-dependent process. Results from another P desorption study indicated that the amounts of DTPA-TEA-CaCl2 (pH 7.3) extractable substrate P increased with temperature. The DTPA-extracted P data from the 30 tailing samples over a period of 1 to 48 hours were best described by an empirical first-order-rate equation using t0.5 instead of t as the time variable. Liming and P fertilization were determinant factors for the growth of corn in acid sulfide tailings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".